41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business management services. Training services, namely, providing information and
education regarding workflow management software that
automates business processes. Consultation services in the field of computer software
installation, configuration, customization, optimization and
integration with client systems; computer software design
and development services; technical support services in the
field of computers and networks, namely, troubleshooting of
computer software problems, monitoring of technological
functions and performance of network systems; providing
temporary use of online non-downloadable workflow management
software to automate business processes and labor intensive,
muti-step tasks across systems and data sources.
2.
AUTOMATED TRANSFORMATION OF INFORMATION FROM IMAGES TO TEXTUAL REPRESENTATIONS, AND APPLICATIONS THEREFOR
Recent developments in machine learning (commonly coined “artificial intelligence” or “AI”) have vastly expanded applications for this technology, such as myriad “chat” agents adept at understanding natural human language. While state of the art generative models can parse text queries from a user and provide comprehensive, accurate responses (including generating images depicting desired content), current implementations struggle with understanding all information present in images of documents, especially images of business documents. In particular, generative models fail to understand structured and semi-structured information, e.g., as indicated by graphical information such as lines, geometric relationships (e.g., indicated by tables, graphs, figures, etc.), formatting, and other contextual information that human readers easily and implicitly understand. The disclosed inventive concepts transform structured and semi-structured information along with textual content into a textual representation that allows generative models to better understand textual content and non-textual structured information present in document images.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software and related hardware, namely, servers, and
computer programs for use in developing computer software,
for information capture and information processing, namely,
managing, scanning, collecting, capturing, performing
optical character recognition, extracting, manipulating,
sorting, indexing, classifying, storing, transmitting,
receiving, displaying and transforming images, text and data
on multi-function devices, mobile devices, a computer, or
network of computers, over local, national and global
information networks; unified messaging software and
hardware for emails, fax, voicemail, video, telegraphy, SMS
(short messaging services), MMS (multi media message
service), VoIP (voice over internet protocol), landline and
mobile telephony; software and hardware related to fax
transmissions and ERP (enterprise resource planning);
software applications to automate business processes
(including accounts payable processes) and labor intensive,
multi-step tasks across systems and data sources; global
proprietary digital network servers for the secure exchange
of electronic invoices; software application to create,
view, edit, manipulate, encrypt, collaborate, print,
digitally sign and manage PDF documents; software
applications related to sending print data from mobile
devices, computer workstations or other business
applications and processes to printers and multifunction
devices, holding documents in a secure queue, document
transformation and manipulation, document release, recording
metadata related to the print or moving the print
information into other business processes. Consultation services in the field of computer software
installation, configuration and optimization and integration
with client systems; computer software design and
development services; technical support services in the
field of computers and networks, namely, troubleshooting of
computer hardware and computer software problems, monitoring
of network systems and performance.
4.
AUTOMATED DOCUMENT PROCESSING FOR DETECTING, EXTRACTNG, AND ANALYZING TABLES AND TABULAR DATA
According to one embodiment, a computer-implemented method for detecting and classifying columns of tables and/or tabular data arrangements within image data includes: detecting one or more tables and/or one or more tabular data arrangements within the image data; extracting the one or more tables and/or the one or more tabular data arrangements from the processed image data; and classifying either: a plurality of columns of the one or more extracted tables; a plurality of columns of the one or more extracted tabular data arrangements; or both the columns of the one or more extracted tables and the columns of the one or more extracted tabular data arrangements. Corresponding systems and computer program products are also disclosed.
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Business management services.
(2) Training services, namely, providing information and education regarding workflow management software that automates business processes.
(3) Consultation services in the field of computer software installation, configuration, customization, optimization and integration with client systems; computer software design and development services; technical support services in the field of computers and networks, namely, troubleshooting of computer software problems, monitoring of technological functions and performance of network systems; providing temporary use of online non-downloadable workflow management software to automate business processes and labor intensive, muti-step tasks across systems and data sources.
6.
AUTOMATED TRANSFORMATION OF INFORMATION FROM IMAGES TO TEXTUAL REPRESENTATIONS, AND APPLICATIONS THEREFOR
Recent developments in machine learning (commonly coined "artificial intelligence" or "AI") have vastly expanded applications for this technology, such as myriad "chat" agents adept at understanding natural human language. While state of the art generative models can parse text queries from a user and provide comprehensive, accurate responses (including generating images depicting desired content), current implementations struggle with understanding all information present in images of documents, especially images of business documents. In particular, generative models fail to understand structured and semi-structured information, e.g., as indicated by graphical information such as lines, geometric relationships (e.g., indicated by tables, graphs, figures, etc.), formatting, and other contextual information that human readers easily and implicitly understand. The disclosed inventive concepts transform structured and semi-structured information along with textual content into a textual representation that allows generative models to better understand textual content and non-textual structured information present in document images.
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business management services Training services in the field of workflow management software that automates business processes Consultation services in the field of computer software installation, configuration, customization, optimization and integration with client systems; Computer software design and development services; Technical support services in the field of computers and networks, namely, troubleshooting of computer software problems, monitoring of technological functions and performance of network systems; providing temporary use of online non-downloadable workflow management software to automate business processes and labor intensive, muti-step tasks across systems and data sources
8.
Automated transformation of information from images to textual representations, and applications therefor
Recent developments in machine learning (commonly coined “artificial intelligence” or “AI”) have vastly expanded applications for this technology, such as myriad “chat” agents adept at understanding natural human language. While state of the art generative models can parse text queries from a user and provide comprehensive, accurate responses (including generating images depicting desired content), current implementations struggle with understanding all information present in images of documents, especially images of business documents. In particular, generative models fail to understand structured and semi-structured information, e.g., as indicated by graphical information such as lines, geometric relationships (e.g., indicated by tables, graphs, figures, etc.), formatting, and other contextual information that human readers easily and implicitly understand. The disclosed inventive concepts transform structured and semi-structured information along with textual content into a textual representation that allows generative models to better understand textual content and non-textual structured information present in document images.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Computer software and related hardware, namely, servers, and computer programs for use in developing computer software, for information capture and information processing, namely, managing, scanning, collecting, capturing, performing optical character recognition, extracting, manipulating, sorting, indexing, classifying, storing, transmitting, receiving, displaying and transforming images, text and data on multi-function devices, mobile devices, a computer, or network of computers, over local, national and global information networks; unified messaging software and hardware for emails, fax, voicemail, video, telegraphy, SMS (short messaging services), MMS (multi media message service), VoIP (voice over internet protocol), landline and mobile telephony; software and hardware related to fax transmissions and ERP (enterprise resource planning); software applications to automate business processes (including accounts payable processes) and labor intensive, multi-step tasks across systems and data sources; global proprietary digital network servers for the secure exchange of electronic invoices; software application to create, view, edit, manipulate, encrypt, collaborate, print, digitally sign and manage PDF documents; software applications related to sending print data from mobile devices, computer workstations or other business applications and processes to printers and multifunction devices, holding documents in a secure queue, document transformation and manipulation, document release, recording metadata related to the print or moving the print information into other business processes. (1) Consultation services in the field of computer software installation, configuration and optimization and integration with client systems; computer software design and development services; technical support services in the field of computers and networks, namely, troubleshooting of computer hardware and computer software problems, monitoring of network systems and performance.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software and related hardware, namely, servers, and downloadable computer programs for use in developing computer software, all of the foregoing relating to workflow automation; Computer hardware and downloadable software for unified messaging, namely, for sending and receiving communications via fax, voicemail, video, telegraphy, SMS (short messaging services), MMS (multi media message service), VoIP (voice over internet protocol), landline and mobile telephony, all of the foregoing relating to workflow automation; Computer hardware and downloadable software fax transmissions, all of the foregoing relating to workflow automation; Downloadable ERP (enterprise resource planning) software, all of the foregoing relating to workflow automation; Downloadable workflow management software applications to automate business processes and labor intensive, muti-step tasks across systems and data sources, all of the foregoing relating to workflow automation; Downloadable software application to create, view, edit, manipulate, encrypt, collaborate, print, digitally sign and manage PDF documents, all of the foregoing relating to workflow automation; Downloadable software applications for sending print data from mobile devices, computer workstations or other business applications and processes to printers and multifunction devices, and for holding documents in a secure print queue, document transformation and manipulation being document editing, and for recording metadata related to the foregoing functions, all of the foregoing relating to workflow automation Consultation services in the field of computer software installation, configuration and optimization and integration with client systems; Computer software design and development services; Technical support services in the field of computers and networks, namely, troubleshooting of computer software problems, monitoring of technological functions and performance of network systems
11.
Determining functional and descriptive elements of application images for intelligent screen automation
The presently disclosed inventive concepts are directed to systems, computer program products, and methods for intelligent screen automation. According to one embodiment, a method includes: determining one or more logical relationships between textual elements and non-textual elements of one or more images of a user interface; building a hierarchy comprising some or all of the non-textual elements and some or all of the textual elements in order to form a data structure representing functionality of the user interface; and outputting the data structure to a memory.
G06V 10/34 - Smoothing or thinning of the patternMorphological operationsSkeletonisation
G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
A computer program product for detecting an object depicted in a digital image includes: a computer readable storage medium; and program instructions configured to cause a processor to perform a method comprising: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.
G06T 3/00 - Geometric image transformations in the plane of the image
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
According to one aspect, a computer-implemented method of discovering processes for robotic process automation (RPA) includes: recording a plurality of event streams, each event stream corresponding to a human user interacting with a computing device to perform one or more tasks; concatenating the event streams; segmenting some or all of the concatenated event streams to generate one or more application traces performed by the user interacting with the computing device, each application trace corresponding to one of the one or more tasks performed by the user; clustering the traces according to a task type; identifying, from among some or all of the clustered traces, one or more candidate processes for robotic automation; prioritizing the candidate processes; and selecting at least one of the prioritized candidate processes for robotic automation. Corresponding systems and computer program products are also described.
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
G06F 18/23213 - Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
For table structure recognition in document processing, a methodology can use 2-click human interaction to define bounding box of the table and convert OCR data into n-dim positioning for column-wise and row-wise assignment. An adaptive filter can identify and assign column-like morphologies in tables. An adaptive cycle based column/row assignment can select best methodology for each table. Column overlap and merge detection can use post-processing for complex table structures. Data storage and feedback mechanisms can be used for adaptive template predictions.
A machine learning based key-value extraction model extracts fields/entities from documents. The input images are processed through OCR. A list of words (uni-grams) and their coordinates are extracted from the original images. Following word cleaning and manipulation, n-gram creation (multi-words), and feature engineering, the transformed data is fed into a classification algorithm to predict if a uni-gram or n-gram is one of the target entities or a non-entity. Following the first step that includes unique feature engineering, a second step improves extraction accuracy among the fields/entities.
Systems, methods and computer program products for detecting objects using a multi-detector are disclosed, according to various embodiments. In one aspect, a computer-implemented method includes defining analysis profiles, where each analysis profile: corresponds to one of a plurality of detectors, and comprises: a unique set of analysis parameters and/or a unique detection algorithm. The method further includes analyzing image data in accordance with the analysis profiles; selecting an optimum analysis result based on confidence scores associated with different analysis results; and detecting objects within the optimum analysis result. According to additional aspects, the analysis parameters may define different subregions of a digital image to be analyzed; a composite analysis result may be generated based on analysis of the different subregions by different detectors; and the optimum analysis result may be based on the composite analysis result.
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/90 - Determination of colour characteristics
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 20/40 - ScenesScene-specific elements in video content
G06V 30/146 - Aligning or centering of the image pick-up or image-field
According to one embodiment, a computer-implemented method for detecting and classifying columns of tables and/or tabular data arrangements within image data includes: detecting one or more tables and/or one or more tabular data arrangements within the image data; extracting the one or more tables and/or the one or more tabular data arrangements from the processed image data; and classifying either: a plurality of columns of the one or more extracted tables; a plurality of columns of the one or more extracted tabular data arrangements; or both the columns of the one or more extracted tables and the columns of the one or more extracted tabular data arrangements. Corresponding systems and computer program products are also disclosed.
Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/90 - Determination of colour characteristics
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 20/40 - ScenesScene-specific elements in video content
The presently disclosed inventive concepts are directed to systems, computer program products, and methods for intelligent screen automation. According to one embodiment, a method includes: determining one or more logical relationships between textual elements and non-textual elements of one or more images of a user interface; building a hierarchy comprising some or all of the non-textual elements and some or all of the textual elements in order to form a data structure representing functionality of the user interface; and outputting the data structure to a memory.
G06V 10/56 - Extraction of image or video features relating to colour
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/50 - Extraction of image or video features by performing operations within image blocksExtraction of image or video features by using histograms, e.g. histogram of oriented gradients [HoG]Extraction of image or video features by summing image-intensity valuesProjection analysis
G06V 10/34 - Smoothing or thinning of the patternMorphological operationsSkeletonisation
20.
Automated document processing for detecting, extracting, and analyzing tables and tabular data
According to one embodiment, a computer-implemented method for classifying one or more tables and/or one or more tabular data arrangements depicted in image data includes: training a machine learning model, using a training dataset representing a plurality of different tables and/or tabular data arrangements, based at least in part on a plurality of recognized textual elements within the training dataset; and outputting a trained classification model based on the training, wherein the trained classification model is configured to classify one or more tables and/or one or more tabular data arrangements represented within a test dataset according to: one or more table classifications; one or more tabular data arrangement classifications; and/or one or more column classifications; and classifying the one or more tables and/or the one or more tabular data arrangements represented within the test dataset using the trained classification model. Methods for detecting, extracting, and classifying tables are also disclosed.
According to one embodiment, a method for detecting, extracting information from, and classifying tables within an original image includes: pre-processing the original image to generate processed image data; detecting one or more tables within the processed image data; extracting the one or more tables from the processed image data; and classifying either: the one or more extracted tables; portions of the one or more extracted tables; or a combination thereof. Additional techniques for pre-processing image data to facilitate detection, extraction of information from, and classification of tables (or portions thereof) are also featured. Corresponding systems and computer program products are included in the scope of the invention. The inventive concepts are also applicable to tabular data arrangements that may not fit a strict definition of a “table.”
According to one aspect, a computer-implemented method of discovering processes for robotic process automation (RPA) includes: recording a plurality of event streams, each event stream corresponding to a human user interacting with a computing device to perform one or more tasks; concatenating the event streams; segmenting some or all of the concatenated event streams to generate one or more individual traces performed by the user interacting with the computing device, each trace corresponding to a particular task; clustering the traces according to a task type; identifying, from among some or all of the clustered traces, one or more candidate processes for robotic automation; prioritizing the candidate processes; and selecting at least one of the prioritized candidate processes for robotic automation. Further aspects building upon the above include generating RPA models to perform tasks determined to be processes for RPA. Corresponding systems and computer program products are also described.
G06F 18/23213 - Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
23.
Analytic systems, methods, and computer-readable media for structured, semi-structured, and unstructured documents
A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.
Techniques for binarization and extraction of information from image data are disclosed. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; and extracting data from some or all of the plurality of binarized images. The extracted data includes connected components that overlap and/or are obscured by unique background. Corresponding systems and computer program products are disclosed.
G06T 7/187 - SegmentationEdge detection involving region growingSegmentationEdge detection involving region mergingSegmentationEdge detection involving connected component labelling
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
25.
Object detection and image cropping using a multi-detector approach
Systems, methods and computer program products for detecting objects using a multi-detector are disclosed, according to various embodiments. In one aspect, a computer-implemented method includes defining an analysis profile comprising an initial number of analysis cycles dedicated to each of a plurality of detectors, where each detector is independently configured to detect objects according to a unique set of analysis parameters and/or a unique detector algorithm. The method also includes: receiving digital video data that depicts at least one object; analyzing the digital video data using some or all of the detectors in accordance with the analysis profile, where the analyzing produces an analysis result for each detector used in the analysis. Further, the method includes updating the analysis profile by adjusting the number of analysis cycles dedicated to at least one of the detectors based on the analysis results.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 20/40 - ScenesScene-specific elements in video content
G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 30/413 - Classification of content, e.g. text, photographs or tables
The presently disclosed inventive concepts are directed to systems, computer program products, and methods for intelligent screen automation. The inventive computer program products include program instructions configured to cause a computer, upon execution thereof, to perform a method including: identifying, from among a plurality of elements within one or more images of a user interface, a first set of elements and a second set of elements, wherein the first set of elements and the second set of elements each independently comprise either or both of: textual elements, and non-textual elements; determining one or more logical relationships between the textual elements and the non-textual elements; building a hierarchy comprising some or all of the first set of elements and some or all of the second set of elements, wherein building the hierarchy forms a data structure representing functionality of the user interface; and outputting the data structure to a memory.
A computer-implemented method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.
G06T 3/00 - Geometric image transformations in the plane of the image
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; optionally sampling color information from a second plurality of pixels of the digital image, wherein each of the second plurality of pixels is located in a foreground region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 20/40 - ScenesScene-specific elements in video content
According to an exemplary embodiment, a method for pre-cropping digital image data includes: dividing the digital image into segments; computing a color value distance between corresponding pixels of neighboring segments of the digital image; comparing the color value distance(s) against a minimum color distance threshold; clustering neighboring segments having a color value distance less than or equal to the minimum color distance threshold; computing a connected structure based on the clustered segments; computing a polygon bounding the connected structure; comparing a fraction of segments included in the connected structure and the polygon, relative to a total number of segments in the digital image, to a minimum included segment threshold; and in response to determining the fraction of segments in the connected structure and the polygon, relative to the total number of segments meets or exceeds a minimum included segment threshold, cropping the digital image based on edges of the polygon.
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 20/40 - ScenesScene-specific elements in video content
A method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
G06T 3/00 - Geometric image transformations in the plane of the image
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 30/418 - Document matching, e.g. of document images
31.
Content-based detection and three dimensional geometric reconstruction of objects in image and video data
Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed. The concepts utilize internal features for detection and reconstruction, avoiding reliance on information derived from location of edges. The inventive concepts provide an improvement over conventional techniques since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, detecting a document depicted in a digital image includes: detecting a plurality of identifying features of the document, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of one or more edges of the document based at least in part on the plurality of identifying features; and outputting the projected location of the one or more edges of the document to a display of a computer, and/or a memory.
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
G06T 3/00 - Geometric image transformations in the plane of the image
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
G06V 30/418 - Document matching, e.g. of document images
32.
Systems and methods for mobile image capture and processing
In several embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The techniques include capturing image data depicting a document; defining a plurality of candidate edge points within the image data; and defining four sides of a tetragon based on at least some of the plurality of candidate edge points; wherein each side of the tetragon corresponds to a different side of the document; wherein an area of the tetragon comprises at least a threshold percentage of a total area of the digital image; and wherein the tetragon bounds the digital representation of the document.
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06T 3/00 - Geometric image transformations in the plane of the image
H04N 1/387 - Composing, repositioning or otherwise modifying originals
G06T 7/143 - SegmentationEdge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computerOutput arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
According to one aspect, a computer-implemented method of discovering processes for robotic process automation (RPA) includes: recording a plurality of event streams, each event stream corresponding to a human user interacting with a computing device to perform one or more tasks; concatenating the event streams; segmenting some or all of the concatenated event streams to generate one or more individual traces performed by the user interacting with the computing device, each trace corresponding to a particular task; clustering the traces according to a task type; identifying, from among some or all of the clustered traces, one or more candidate processes for robotic automation; prioritizing the candidate processes; and selecting at least one of the prioritized candidate processes for robotic automation. Further aspects building upon the above include generating RPA models to perform tasks determined to be processes for RPA. Corresponding systems and computer program products are also described.
Computerized techniques for improved binarization and extraction of information from digital image data are disclosed in accordance with various embodiments. The inventive concepts include rendering a digital image using a plurality of binarization thresholds to generate a plurality of binarized digital images, wherein at least some of the binarized digital images are generated using one or more binarization thresholds that are determined based on a priori knowledge regarding an object depicted in the digital image; identifying one or more connected components within the plurality of binarized digital images; and identifying one or more text regions within the digital image based on some or all of the connected components. Systems and computer program products are also disclosed.
G06T 7/187 - SegmentationEdge detection involving region growingSegmentationEdge detection involving region mergingSegmentationEdge detection involving connected component labelling
G06V 10/28 - Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
The presently disclosed inventive concepts are directed to systems, computer program products, and methods for intelligent screen automation. The inventive techniques include: identifying first and second sets of elements within one or more images of a user interface, where each of the first set of elements is independently selected from: vertical lines, horizontal lines, and rectangular elements, and each of the second set of elements is independently selected from: radio buttons, icons, and textual elements. The methods also include determining one or more logical relationships between the textual elements and non-textual elements of the image; building a hierarchy comprising some or all of the first set of elements and some or all of the second set of elements in order to form a tree-based data structure representing functionality of the user interface; and outputting the tree-based data structure to a memory.
One example of the system and method described herein may provide a universal endpoint address schema to route documents and manage document workflows, which may include one or more encapsulated workflow packages. In particular, a globally unique endpoint address may be specified using the universal endpoint address schema to route documents to any addressable destination and link the documents to workflow steps, processing rules, and business intelligence that can enforce business constraints. Furthermore, the globally unique endpoint address may be specified using the universal endpoint address schema may be linked to tickets that request documents or document-related services from third parties in cloud or virtualized data centers, whereby the universal endpoint address schema may extend the abilities that different organizations have to collaborate with one another.
A method includes setting one or more parameters in a state determiner, each of the one or more parameters being based at least in part on one or more predefined processing events related to one or more queued processing tasks; determining a web page processing state of a browser based at least in part on the one or more parameters in accordance with one or more predefined criteria; and during processing of a web page by means of the browser: tracing predefined processing events that may cause creation of queued processing tasks with associated delays; invoking a delay converter to change the delays by one or more of absolute decrements, relative decrements and proportional decrements; and reducing a time that the start of execution of the one or more queued processing tasks are set to be delayed by the source code of the web page.
Techniques for binarization and extraction of information from image data are disclosed. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; subjecting the region of interest within a digital image to a plurality of thresholding and extraction iterations; and extracting data from some or all of the plurality of binarized images. Corresponding systems and computer program products are disclosed.
Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image; optionally sampling color information from a second plurality of pixels of the digital image; generating or receiving a representative background color profile based on the color information sampled from the first plurality of pixels; generating or receiving a representative foreground color profile based on the color information sampled from the second plurality of pixels and/or the first plurality of pixels; assigning each pixel a label; binarizing the digital image based on the labels; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.
Computerized techniques for real-time object detection from video data include: defining an analysis profile comprising an initial number of analysis cycles dedicated to each of a plurality of detectors, each detector being independently configured to detect objects according to a unique set of analysis parameters; receiving a plurality of frames of digital video data, the digital video data depicting an object; analyzing the plurality of frames using the plurality of detectors and in accordance with the analysis profile, wherein analyzing the plurality of frames produces an analysis result for each of the plurality of detectors; determining a confidence score for each of the analysis results; and updating the analysis profile by adjusting the number of analysis cycles dedicated to at least one of the plurality of detectors based on the confidence scores. Corresponding systems and computer program products are also disclosed.
A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
42.
Content-based object detection, 3D reconstruction, and data extraction from digital images
A method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; projecting a location of region(s) of interest of the object based on the plurality of identifying features, where each region of interest depicts content; building and/or selecting an extraction model configured to extract the content based at least in part on: the location of the region(s) of interest, the of identifying feature(s), or both; and extracting the some or all of the content from the digital image using the extraction model. Corresponding system and computer program product embodiments are disclosed. The inventive concepts enable reliable extraction of data from digital images where portions of an object are obscured/missing, and/or depicted on a complex background.
G06T 3/00 - Geometric image transformations in the plane of the image
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
G06K 9/62 - Methods or arrangements for recognition using electronic means
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
G06K 9/36 - Image preprocessing, i.e. processing the image information without deciding about the identity of the image
Systems, computer program products, and techniques for detecting and/or reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be detected and/or reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, reconstructing an object depicted in a digital image includes using a processor to: detect a plurality of identifying features of the object, where the identifying features are located internally with respect to the object; and reconstruct the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the identifying features.
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
G06T 3/00 - Geometric image transformations in the plane of the image
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/62 - Methods or arrangements for recognition using electronic means
In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The exemplary image processing techniques are coupled with inbound and outbound communications protocols and workflows configured to facilitate closed-loop processing, such that a method includes initiating a workflow; providing one or more of case information and raw data to the workflow; processing one or more of the case information and the raw data to generate a processing result; storing at least some of the case information in association with the processing result, wherein the associated case information acts as an identifier of the processing result; transmitting at least the processing result and the identifier; receiving, in response to the transmitting, a reply comprising the identifier; and retrieving at least the processing result using the identifier.
H04M 1/00 - Substation equipment, e.g. for use by subscribers
G06F 16/583 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
46.
Machine print, hand print, and signature discrimination
Computer program products for discriminating hand and machine print from each other, and from signatures, are disclosed and include program code readable and/or executable by a processor to: receive an image, determine a color depth of the image; reducing the color depth of non-bi-tonal images to generate a bi-tonal representation of the image; identify a set of one or more graphical line candidates in either the bi-tonal image or the bi-tonal representation, the graphical line candidates including true graphical lines and/or false positives; discriminate any of the true graphical lines from any of the false positives; remove the true graphical lines from the bi-tonal image or the bi-tonal representation without removing the false positives to generate a component map comprising connected components and excluding graphical lines; identify one or more of the connected components in the component map; and output and/or display and indicator of each of the connected components.
Computer program products for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer program product includes a computer readable medium having computer readable and/or executable program instructions embodied therewith, the program instructions being configured to cause a processor to: invoke a mobile application using a mobile device; receive auditory input via the mobile device; and perform a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
48.
Mobile document detection and orientation based on reference object characteristics
In various embodiments, computer program products for detecting, estimating, calculating, etc. characteristics of a document based on reference objects depicted on the document are disclosed. In one approach, a computer program product for processing a digital image depicting a document includes instructions executable by a computer for analyzing the digital image to determine one or more of a presence and a location of one or more reference objects; determining one or more geometric characteristics of at least one of the reference objects; defining one or more region(s) of interest based at least in part on one or more of the determined geometric characteristics; and detecting a presence or absence of an edge of the document within each defined region of interest. Additional embodiments leverage the type of document depicted in the image, multiple frames of image data, and/or calculate or extrapolate document edges rather than locating edges in the image.
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
49.
Global geographic information retrieval, validation, and normalization
A computer program product includes program instructions configured to cause a processor, to: perform optical character recognition (OCR) on an image of a document; extract an identifier of the document from the image based at least in part on the OCR; compare at least portions of the identifier with content from one or more reference data sources; and determine whether the identifier is valid based at least in part on the comparison. The content comprises global address information; while the content from the reference is derived from geographic information. Deriving the content from the geographic information includes: obtaining the geographic information; and parsing the geographic information according to a set of predefined heuristic rules, where the heuristic rules are configured to normalize the global address information obtained from the one or more sources according to a single convention for representing address information.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
Systems, methods, and computer program products for smart, automated capture of textual information using optical sensors of a mobile device, and selective provision of such textual information to a user interface for facilitating performance of downstream workflows are disclosed. The capture and provision is context-aware, and determines context of the optical input, and optionally invokes a contextually-appropriate workflow based thereon. The techniques also provide capability to normalize, correct, and/or validate the captured optical input and provide the corrected, normalized, validated, etc. information to the contextually-appropriate workflow. As a result, the overall process of capturing information from optical input using a mobile device, invoking an appropriate workflow, and providing captured information to the workflow is significantly simplified and improved in terms of accuracy of data transfer/entry, speed and efficiency of workflows, and user experience.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
According to one embodiment, a computer-implemented method for cleaning up a data set having a possible incorrect label includes: selecting a plurality of training documents; estimating a quality of an organization of a plurality of categories; and determining whether the quality of the organization is greater than a predetermined quality threshold. Corresponding system and computer program product embodiments are also presented. Other aspects and advantages of the present invention will become apparent from the following detailed description, which, when taken in conjunction with the drawings, illustrate by way of example the principles of the invention.
Systems, computer program products, and techniques for detecting objects depicted in digital image data are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish object detection, thereby avoiding reliance on detecting object edges and/or transitions between the object and other portions of the digital image data, e.g. background textures or other objects. The inventive concepts thus provide an improvement over conventional object detection since objects may be detected even when edges are obscured or not depicted in the digital image data. In one aspect, a computer-implemented method of detecting an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; and projecting a location of one or more edges of the object based at least in part on the plurality of identifying features.
A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.
G06F 17/30 - Information retrieval; Database structures therefor
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
09 - Scientific and electric apparatus and instruments
37 - Construction and mining; installation and repair services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software and hardware; computer software and related hardware, including servers, and computer programs for use in developing computer software, for information capture and information processing, including managing, scanning, collecting, capturing, extracting, manipulating, sorting, indexing, classifying, storing, transmitting, receiving, displaying and transforming images, text and data on a computer, or network of computers, over local, national and global information networks; computer software and hardware for creating, managing and integrating information capture capabilities; unified messaging software and hardware for emails, fax, voicemail, video, telex, SMS, MMS, instant messaging, VoIP, landline, mobile telephony; software and hardware related to fax transmissions and ERP. Consultation services in the field of computer hardware installation; technical support services in the field of computers and networks, including service and repair of computer networks and computer hardware. Consultation services in the field of computer software installation, configuration and optimisation; consultation services in the field of computer hardware configuration and optimisation; computer software design and development services; technical support services in the field of computers and networks, including service and repair of computer software; software as a service (SAAS) services featuring software in the field of information capture, consultancy, information and advisory services relating to all the aforesaid services.
According to one embodiment, a computer-implemented method for confirming/rejecting a most relevant example includes: generating a binary decision model by training a binary classifier using a plurality of training documents; classifying one or more test documents into one of a plurality of categories using the binary decision model, wherein the one or more test documents lack a user-defined category label; selecting a most relevant example of the classified test documents from among the classified test documents; displaying, using a display of the computer, the most relevant example of the classified test documents to a user; receiving, via the computer and from the user, a confirmation or a negation of a classification label of the most relevant example of the classified test documents; and storing the confirmation or the negation of the classification label of the most relevant example of the classified test documents to a memory of the computer.
A method includes: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; analyzing the ID based at least in part on the ID classification; determining at least some identifying information from the ID; at least one of building an ID profile and updating the ID profile, based at least in part on the analysis; providing at least one of the ID and the ID classification to a loan application workflow and/or a new financial account workflow; and driving at least a portion of the workflow based at least in part on the ID and the ID classification. Corresponding systems and computer program products are also disclosed.
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
57.
Building classification and extraction models based on electronic forms
According to one embodiment, a computer-implemented method is configured for building a classification and/or data extraction knowledge base using an electronic form. The method includes: receiving an electronic form having associated therewith a plurality of metadata labels, each metadata label corresponding to at least one element of interest represented within the electronic form; parsing the plurality of metadata labels to determine characteristic features of the element(s) of interest; building a representation of the electronic form based on the plurality of metadata labels; generating a plurality of permutations of the representation of the electronic form by applying a predetermined set of variations to the representation; and training either a classification model, an extraction model, or both using: the representation of the electronic form, and the plurality of permutations of the representation of the electronic form. Corresponding systems and computer program products are also disclosed.
Computerized techniques for improved binarization and extraction of information from digital image data are disclosed in accordance with various embodiments. The inventive concepts include: rendering, using a processor of the mobile device, a digital image using a plurality of binarization thresholds to generate a plurality of range-binarized digital images, wherein each rendering of the digital image is generated using a different combination of the plurality of binarization thresholds; identifying, using the processor of the mobile device, one or more range connected components within the plurality of range-binarized digital images; and identifying, using the processor of the mobile device, a plurality of text regions within the digital image based on some or all of the range connected components. Corresponding systems and computer program products are also disclosed.
According to one embodiment, a system includes a processor and logic in and/or executable by the processor to cause the processor to: initiate a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation; detect a document depicted in the video data; track a position of the detected document throughout the video data; select a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generate a composite image based on at least some of the selected plurality of images.
In one approach, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating the extracted data of interest against reference information stored on the mobile device. In another embodiment, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating authenticity of the document based on comparing some or all of the extracted data of interest to reference information stored on the mobile device.
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/22 - Image acquisition using hand-held instruments
G06K 9/72 - Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognised identity of a number of successive patterns, e.g. a word
H04N 1/32 - Circuits or arrangements for control or supervision between transmitter and receiver
In several embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The techniques include detecting medical documents and/or documents relevant to an insurance claim by defining candidate edge points based on the captured image data and defining four sides of a tetragon based on at least some of the candidate edge points. In the case of an insurance claim process, the techniques also include determining whether the document is relevant to an insurance claim; and in response to determining the document is relevant to the insurance claim, submitting the image data, information extracted from the image data, or both to a remote server for claims processing. The image capture and processing techniques further facilitate processing of medical documents and/or insurance claims with a plurality of additional features that may be used individually or in combination in various embodiments.
G06T 3/00 - Geometric image transformations in the plane of the image
H04N 1/387 - Composing, repositioning or otherwise modifying originals
G06T 7/143 - SegmentationEdge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computerOutput arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
A method includes: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; analyzing the ID based at least in part on the ID classification; determining at least some identifying information from the ID; at least one of building an ID profile and updating the ID profile, based at least in part on the analysis; providing at least one of the ID and the ID classification to a loan application workflow and/or a new financial account workflow; and driving at least a portion of the workflow based at least in part on the ID and the ID classification. Corresponding systems and computer program products are also disclosed.
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
G06Q 20/40 - Authorisation, e.g. identification of payer or payee, verification of customer or shop credentialsReview and approval of payers, e.g. check of credit lines or negative lists
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
In one embodiment, a system includes: a processor; and logic in and/or executable by the processor to cause the processor to: generate a first feature vector based on a digital image captured by a mobile device; compare the first feature vector to a plurality of reference feature matrices; classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison; determine one or more object features of the object based at least in part on the particular object class; and detect one or more additional objects belonging to the particular object class based on the determined object feature(s). The one or more additional objects are depicted either in the digital image or another digital image received by the mobile device. Corresponding computer program products are also disclosed.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/22 - Image acquisition using hand-held instruments
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/36 - Image preprocessing, i.e. processing the image information without deciding about the identity of the image
64.
Systems and methods for detecting and classifying objects in video captured using mobile devices
In one embodiment, a system includes a processor and logic executable by the processor. The logic is configured to cause the processor to: capture video data using a mobile device, the video data comprising a plurality of frames; determine whether one or more of the frames depict a document exhibiting one or more defining characteristics; determine whether one or more of the frame(s) determined to depict the document also satisfy one or more predetermined quality control criteria; and in response to determining one or more of the frames depict the document and also satisfy the one or more predetermined quality control criteria, automatically capture an image of the document. Corresponding computer program products are also disclosed.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
65.
Systems and methods for mobile image capture and processing
In several embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The techniques include detecting medical documents and/or documents relevant to an insurance claim by defining candidate edge points based on the captured image data and defining four sides of a tetragon based on at least some of the candidate edge points. In the case of an insurance claim process, the techniques also include determining whether the document is relevant to an insurance claim; and in response to determining the document is relevant to the insurance claim, submitting the image data, information extracted from the image data, or both to a remote server for claims processing. The image capture and processing techniques further facilitate processing of medical documents and/or insurance claims with a plurality of additional features that may be used individually or in combination in various embodiments.
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06T 3/00 - Geometric image transformations in the plane of the image
H04N 1/387 - Composing, repositioning or otherwise modifying originals
G06T 7/143 - SegmentationEdge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computerOutput arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
Techniques for improved binarization and extraction of information from digital image data are disclosed in accordance with various embodiments. The inventive concepts include independently binarizing portions of the image data on the basis of individual features, e.g. per connected component, and using multiple different binarization thresholds to obtain the best possible binarization result for each portion of the image data independently binarized. Determining the quality of each binarization result may be based on attempted recognition and/or extraction of information therefrom. Independently binarized portions may be assembled into a contiguous result. In one embodiment, a method includes: identifying a region of interest within a digital image; generating a plurality of binarized images based on the region of interest using different binarization thresholds; and extracting data from some or all of the plurality of binarized images. Corresponding systems and computer program products are also disclosed.
Determining a web page processing state of a browser, during a processing of a web page using a browser, by setting parameters in a state determiner on the basis of predefined processing events related to queued processing tasks; the state determiner determining said web page processing state on the basis of said parameters in accordance with one or more predefined criteria.
Systems, computer program products, and techniques for reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, a computer-implemented method of reconstructing an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; and reconstructing the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the plurality of identifying features.
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
G06T 3/00 - Geometric image transformations in the plane of the image
G06K 9/46 - Extraction of features or characteristics of the image
G06K 9/62 - Methods or arrangements for recognition using electronic means
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
According to one embodiment, a computer-implemented method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting an identifier of the document from the image based at least in part on the OCR; comparing the identifier with content from one or more reference data sources, wherein the content from the one or more reference data sources comprises global address information; and determining whether the identifier is valid based at least in part on the comparison. The method may optionally include normalizing the extracted identifier, retrieving additional geographic information, correcting OCR errors, etc. based on comparing extracted information with reference content. Corresponding systems and computer program products are also disclosed.
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06F 17/30 - Information retrieval; Database structures therefor
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/03 - Detection or correction of errors, e.g. by rescanning the pattern
G06K 9/48 - Extraction of features or characteristics of the image by coding the contour of the pattern
Systems, methods, and computer program products are disclosed for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer-implemented method for performing a touchless mobile workflow includes: invoking a mobile application using a mobile device; receiving auditory input via the mobile device; and performing a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.
G06K 9/72 - Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognised identity of a number of successive patterns, e.g. a word
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
Techniques for capturing long document images and generating composite images therefrom include: detecting a document depicted in image data; tracking a position of the detected document within the image data; selecting a plurality of images, wherein the selection is based at least in part on the tracked position of the detected document; and generating a composite image based on at least one of the selected plurality of images. The tracking and selection are optionally but preferably based in whole or in part on motion vectors estimated at least partially based on analyzing image data such as test and reference frames within the captured video data/images. Corresponding systems and computer program products are also disclosed.
In one embodiment, a method includes receiving a digital image captured by a mobile device; and using a processor of the mobile device: generating a first representation of the digital image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing; and determining one or more object features of the object based at least in part on the particular object class. Corresponding systems and computer program products are also disclosed.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/22 - Image acquisition using hand-held instruments
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/36 - Image preprocessing, i.e. processing the image information without deciding about the identity of the image
73.
Selective, user-mediated content recognition using mobile devices
A method includes: displaying a digital image on a first portion of a display of a mobile device; receiving user feedback via the display of the mobile device; analyzing the user feedback to determine a meaning of the user feedback; based on the determined meaning of the user feedback, analyzing a portion of the digital image corresponding to either the point of interest or the region of interest to detect one or more connected components depicted within the portion of the digital image; classifying each detected connected component depicted within the portion of the digital image; estimating an identity of each detected connected component based on the classification of the detected connected component; and one or more of: displaying the identity of each detected connected component on a second portion of the display of the mobile device; and providing the identity of each detected connected component to a workflow.
Systems, methods, and computer program products for smart, automated capture of textual information using optical sensors of a mobile device are disclosed. The capture and provision is context-aware, and determines context of the optical input, and invokes a contextually-appropriate workflow based thereon. The techniques also provide capability to normalize, correct, and/or validate the captured optical input and provide the corrected, normalized, validated, etc. information to the contextually-appropriate workflow. Other information necessary by the workflow and available to the mobile device optical sensors may also be captured and provided, in a single automatic process. As a result, the overall process of capturing information from optical input using a mobile device, invoking an appropriate workflow, and providing captured information to the workflow is significantly simplified and improved in terms of accuracy of data transfer/entry, speed and efficiency of workflows, and user experience.
G06K 9/72 - Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognised identity of a number of successive patterns, e.g. a word
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
A computer system extracts contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored semi-structured document(s) and/or one or more electronically stored unstructured document(s). The computer system performs a multi-dimensional analysis to narrow the universe of contender values from all words on a page of the compilation to the contender value(s) with the highest likelihood of being associated with the pre-defined value. The system's platform allows every user of the system to customize the system according to the user's needs. Various aspects can enable users to mine document stores for information that can be charted, graphed, studied, and compared to help make better decisions.
A scanning system provides for scanning documents and generating respective electronic copies with associated metadata. A scanner scans one or more documents to produce respective electronic copies. A user interface captures metadata entered by a user regarding the documents. A controller is communicatively coupled to the scanner and the user interface, and enables the user interface to capture the metadata concurrently with the scanner's scanning the documents. The electronic copy and the metadata can be associated with one another or incorporated into a common file. Parallel metadata entry and physical scanning reduces time a user spends to perform the overall process, resulting in increased user satisfaction.
In various embodiments, methods, systems, and computer program products for detecting, estimating, calculating, etc. characteristics of a document based on reference objects depicted on the document are disclosed. In one approach, a computer-implemented method for processing a digital image depicting a document includes analyzing the digital image to determine one or more of a presence and a location of one or more reference objects; determining one or more geometric characteristics of at least one of the reference objects; defining one or more region(s) of interest based at least in part on one or more of the determined geometric characteristics; and detecting a presence or an absence of an edge of the document within each defined region of interest. Additional embodiments leverage the type of document depicted in the image, multiple frames of image data, and/or calculate or extrapolate document edges rather than locating edges in the image.
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
78.
Systems and methods for improving video captured using mobile devices
Systems, methods, and computer program products for capturing and analyzing image data, preferably video data, are disclosed. The inventive concepts include using multiple frames of image data to generate a composite image, where the composite image may be characterized by a higher resolution than one or more of the individual frames used to generate the composite image, and/or absence of a blurred region present in one or more of the individual frames. Inventive techniques also include determining a minimum capture resolution appropriate for capturing images of particular objects for downstream processing, and optionally triggering generation of a composite image having sufficient resolution to facilitate the downstream processing in response to detecting one or more frames of image data are characterized by a resolution, and/or a region having a resolution, less than the minimum capture resolution appropriate for capturing images of those particular objects.
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
In various embodiments, methods, systems, and computer program products for determining distance between an object and a capture device are disclosed. The distance determination techniques are based on image data captured by the capture device, where the image data represent the object. These techniques improve the function of capture devices such as mobile phones by enabling determination of distance using a single lens capture device, and based on intrinsic parameters of the capture device, such as focal length and scaling factor(s), in preferred approaches. In some approaches, the distance estimation may be based in part on a priori knowledge regarding size of the object represented in the image data. Distance determination may be based on a homography transform and/or reference image data representing the object, a same type or similar type of object, in more approaches.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/52 - Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
G06T 3/00 - Geometric image transformations in the plane of the image
G01B 11/14 - Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
An efficient method and system to enhance digital acquisition devices for analog data is presented. The enhancements offered by the method and system are available to the user in local as well as in remote deployments yielding efficiency gains for a large variety of business processes. The quality enhancements of the acquired digital data are achieved efficiently by employing virtual reacquisition. The method of virtual reacquisition renders unnecessary the physical reacquisition of the analog data in case the digital data obtained by the acquisition device are of insufficient quality. The method and system allows multiple users to access the same acquisition device for analog data. In some embodiments, one or more users can virtually reacquire data provided by multiple analog or digital sources. The acquired raw data can be processed by each user according to his personal preferences and/or requirements. The preferred processing settings and attributes are determined interactively in real time as well as non real time, automatically and a combination thereof.
A method includes receiving user input defining a workflow comprising one or more activities and one or more rules; receiving user input defining a user interface (UI) configured to facilitate a user performing the workflow at least in part using a processor of a mobile device; and generating a mobile software application based on the workflow and the UI. In another embodiment, a method includes: instantiating a mobile application on a mobile device; launching a workflow within the mobile application, the workflow comprising one or more activities and one or more rules; rendering one or more user interfaces based at least in part on the workflow; displaying at least one of the user interfaces on a display of the mobile device; receiving user input via at least one of the user interfaces; and modifying the workflow based at least partially on user input. Systems and computer program products are also disclosed.
G06F 17/30 - Information retrieval; Database structures therefor
G06F 9/44 - Arrangements for executing specific programs
G06Q 10/06 - Resources, workflows, human or project managementEnterprise or organisation planningEnterprise or organisation modelling
H04W 4/02 - Services making use of location information
G06F 8/38 - Creation or generation of source code for implementing user interfaces
G06Q 40/02 - Banking, e.g. interest calculation or account maintenance
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
Initiating document management in an enterprise network from outside of the network can challenge information technology (IT) specialists because many solutions require altering security of the enterprise network. In an embodiment, a method includes polling, from an automated agent in an agent-side network, a server in a cloud-side network for a request to access a document management resource of the agent-side network via an interface between the agent-side network and cloud-side network The method further includes, responsive to the polling, downloading the request via the interface between the agent-side network and the cloud-side network. The method additionally includes issuing the request to the document management resource to cause the document management resource to access a document stored on a device of the agent-side network and perform an operation associated with the request. The method, therefore, enables a user access to the document management resource from outside of an enterprise network.
Systems, computer program products, and techniques for discriminating hand and machine print from each other, and from signatures, are disclosed and include determining a color depth of an image, the color depth corresponding to at least one of grayscale, bi-tonal and color; reducing color depth of non-bi-tonal images to generate a bi-tonal representation of the image; identifying a set of one or more graphical line candidates in either the bi-tonal image or the bi-tonal representation, the graphical line candidates including one or more of true graphical lines and false positives; discriminating any of the true graphical lines from any of the false positives; removing the true graphical lines from the bi-tonal image or the bi-tonal representation without removing the false positives to generate a component map comprising connected components and excluding graphical lines; and identifying one or more of the connected components in the component map.
Systems and methods for mobile image data capture and processing are disclosed. The techniques encompass receipt or capture of digital image data, detecting an object such as a document depicted in a digital image corresponding to the digital image data, processing the digital image to improve image quality, classifying the object from the processed image data, and extracting useful information from the object. Processing may improve image quality by correcting artifacts such as distortion, skew, blur, shadows, etc. common to digital images captured using mobile devices. Classification is based on identifying unique features (and/or combinations thereof) within the image data and determining whether the identified features indicate the object belongs to a class of known objects having similar characteristics, or is unique to all known classes. Extraction is based in whole or in part on object classification. All operations may be performed using mobile technology exclusively.
In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The exemplary image processing techniques are coupled with inbound and outbound communications protocols and workflows configured to facilitate closed-loop processing, such that a method includes initiating a workflow; providing one or more of case information and raw data to the workflow; processing one or more of the case information and the raw data to generate a processing result; storing at least some of the case information in association with the processing result, wherein the associated case information acts as an identifier of the processing result; transmitting at least the processing result and the identifier; receiving, in response to the transmitting, a reply comprising the identifier; and retrieving at least the processing result using the identifier.
In various embodiments, methods, systems, and computer program products for capturing and processing digital images captured by a mobile device are disclosed. In one embodiment, a method includes capturing image data using a mobile device, the image data depicting a digital representation of a document; defining, based on the image data, a plurality of candidate edge points corresponding to the document; defining four sides of a tetragon based on at least some of the plurality of candidate edge points; determining a plurality of fields within the tetragon; for each field, determining at least a field location and a field data type; associating each determined field location with each field data type to generate a plurality of metadata labels; and associating the plurality of metadata labels with an image of an electronic form.
In one approach, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating the extracted data of interest against reference information stored on the mobile device. In another embodiment, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating authenticity of the document based on comparing some or all of the extracted data of interest to reference information stored on the mobile device.
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/22 - Image acquisition using hand-held instruments
G06K 9/72 - Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognised identity of a number of successive patterns, e.g. a word
G06K 9/32 - Aligning or centering of the image pick-up or image-field
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
The present invention relates to a camera based method for text input and detection of a keyword or of a text-part within page or a screen comprising the steps of: directing a camera module on the printed page and capturing an image thereof; digital image filtering of the captured image; detection of word blocks contained in the image, each word block containing most likely a recognizable word; performing OCR within each word block; determination of A-blocks among the word blocks according to a keyword probability determination rule, wherein each of the A-blocks contains most likely the keyword; assignment of an attribute to each A-block; indication of the A-blocks in the display by a frame or the like for a further selection of the keyword; further selection of the A-block containing the keyword based on the displayed attribute of the keyword; forwarding the text content as text input to an application.
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/32 - Aligning or centering of the image pick-up or image-field
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
H04N 1/32 - Circuits or arrangements for control or supervision between transmitter and receiver
A method includes: capturing or receiving at least one image of one or more identity documents (IDs) using a mobile device; determining identifying information from one or more of the IDs; building an ID profile based on the identifying information; storing the ID profile to a memory of the mobile device; invoking a workflow configured to facilitate a business transaction; detecting a predetermined stimulus in the workflow, the stimulus relating to the business transaction; providing at least a portion of the ID profile to the workflow in response to detecting the predetermined stimulus; and driving at least a portion of the workflow using the provided portion of the ID profile. Related systems and computer program products are also disclosed.
A method is provided for organizing data sets. In use, an automatic decision system is created or updated for determining whether data elements fit a predefined organization or not, where the decision system is based on a set of preorganized data elements. A plurality of data elements is organized using the decision system. At least one organized data element is selected for output to a user based on a score or confidence from the decision system for the at least one organized data element. Additionally, at least a portion of the at least one organized data element is output to the user. A response is received from the user comprising at least one of a confirmation, modification, and a negation of the organization of the at least one organized data element. The automatic decision system is recreated or updated based on the user response. Other embodiments are also presented.
Systems, methods, and computer program products for smart, automated capture of textual information using optical sensors of a mobile device are disclosed. The textual information is provided to a mobile application or workflow without requiring the user to manually enter or transfer the data without requiring user intervention such as a copy/paste operation. The capture and provision context-aware, and can normalize or validate the captured textual information prior to entry in the workflow or mobile application. Other information necessary by the workflow and available to the mobile device optical sensors may also be captured and provided, in a single automatic process. As a result, the overall process of capturing information from optical input using a mobile device is significantly simplified and improved in terms of accuracy of data transfer/entry, speed and efficiency of workflows, and user experience.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
A method includes receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; building an extraction model based on the ID classification; extracting data from the ID based on the extraction model; building an ID profile based on the extracted data; storing the ID profile to a memory of the mobile device; detecting a predetermined stimulus in a workflow; identifying workflow-relevant data in the stored ID profile at least partially in response to detecting the predetermined stimulus; providing the workflow-relevant data from the stored ID profile to the workflow; and driving at least a portion of the workflow using the workflow-relevant data. Related systems and computer program products are also disclosed.
A method involves: receiving an image comprising an ID; iteratively classifying the ID; and driving at least a portion of a workflow based at least in part on the classifying; wherein at least some of the classification iterations are based at least in part on comparing feature vector data, wherein a first classification iteration comprises determining the ID belongs to a particular class, and wherein each classification iteration subsequent to the first classification iteration comprises determining whether the ID belongs to a subclass falling within the particular class to which the ID was determined to belong in a prior classification iteration. Related systems and computer program products are also disclosed.
Systems, methods, and computer program products are disclosed and include: initiating a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation. The systems, techniques, and computer program products also include detecting a document depicted in the video data; tracking a position of the detected document throughout the video data; selecting a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generating a composite image based on at least some of the selected plurality of images.
According to one embodiment, a method includes: capturing an image of a financial document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the financial document; extracting an identifier of the financial document from the image based at least in part on the OCR; associating the image of the financial document with metadata descriptive of one or more of the financial document and financial information relating to the financial document; and storing the image of the financial document and the associated metadata to a memory of the mobile device. Exemplary systems and computer program products are also disclosed.
G06K 9/62 - Methods or arrangements for recognition using electronic means
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
96.
Systems and methods for mobile image capture and processing
In various embodiments, methods, systems, and computer program products for capturing and processing digital images captured by a mobile device are disclosed. The claimed algorithms are specifically configured to perform and facilitate loan application processing by capturing an image of a document using a mobile device, and analyzing the image (optionally in conjunction with additional data that may also be captured, determined, or otherwise provided to the loan application process) to determine loan-relevant information. Select loan-relevant information may be extracted, compiled, and/or analyzed to facilitate processing of the loan application. Feedback may be provided to facilitate facile application processing, e.g. by ensuring all requisite information is submitted with the loan application. Image capture and document detection are preferably performed using the mobile device, while all other functions may be performed using the mobile device, a remote server, or some combination thereof.
In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner, or multifunction peripheral. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.
In one example, we describe a method and system for displaying the Printing Preferences UI and graphical user interface and for the dynamic multilingual print driver. In one example, the system determines the language of the currently-logged-in user. In one example, the system determines the supported language that most closely matches the user's language. If unable to match, it uses the system's default language that was set during the initial installation. If that is not available, then it uses English as the language and declares an error (for the user or administrator), because the system has got a corrupted installation. Other details and variations are also presented here.
A system which comprises a server which processes a plurality of financial document transaction requests each having a magnetic ink character recognition (MICR) code and an image of a financial document and a module installed in a portable device having an image sensor, a processor and a transmitter, the module uses the processor to extract a MICR code from a financial document imaged in an image captured using the image sensor and uses the transmitter to forward the MICR code and the image to the server via a network as a financial document transaction request.
G06Q 20/10 - Payment architectures specially adapted for electronic funds transfer [EFT] systemsPayment architectures specially adapted for home banking systems
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G06Q 20/32 - Payment architectures, schemes or protocols characterised by the use of specific devices using wireless devices
100.
Systems and methods for detecting and classifying objects in video captured using mobile devices
A method includes capturing plural frames of video data using a mobile device. The frames are analyzed to determine whether any depict an object exhibiting one or more defining characteristics, and if so, whether those frame(s) depicting the object also satisfy one or more predetermined quality control criteria. If one or more of the frames depict the object and also satisfy the one or more predetermined quality control criteria, the method further includes automatically capturing an image of the object. Exemplary defining characteristics are specified for various types of object, particularly objects comprising documents. Related systems and computer program products are also disclosed. The presently disclosed techniques and systems represent translational developments across the fields of image processing and business process management. Improved analytical techniques enable processing of image captured using cameras rather than traditional scanner technology, and facilitate distribution, tracking and analysis of documents and information throughout business processes.
H04N 1/00 - Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmissionDetails thereof
G06K 9/18 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints using printed characters having additional code marks or containing code marks, e.g. the character being composed of individual strokes of different shape, each representing a different code value
