Kofax, Inc.

American Scientific Materials Technologies, LP

Eastman-kodak Company

Blue Planet Technologies Co., L.p.

Tungsten Automation Corporation

Global 360, Inc.

Kofile Inc.

Alexander Shustorovich

Christopher William Thrasher

Anthony Macciola

Jan Willers Amtrup

Eugene Shustorovich

Konstantin Solntsev

Richard Montano

Yuri Buslaev

Jiyong Ma

Vyacheslav Morgunov

Sergei Myasoedov

Stephen Michael Thompson

Andrei Chernyavsky

Aleksandr Bragin

Nikolai Moiseev

Steve Thompson

Veniamin Kalner

Mauritius A R Schmidtler

Roland G Borrey

Robert A Taylor

Joel S Fechter

Hari Sri Asuri

VEniamin Kalner

Jan W Amtrup

Tim Mortenson

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.

Iterative recognition-guided thresholding and data extraction

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.

Range and/or polarity-based thresholding for improved data extraction

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.

Systems and methods for mobile image capture and processing

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.

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.

Mobile document detection and orientation based on reference object characteristics

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.

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.

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.

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.

Machine print, hand print, and signature discrimination

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.

Systems and methods for classifying objects in digital images captured 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.

Selective, user-mediated content recognition using mobile devices

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.

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.

Determining distance between an object and a capture device based on captured image data

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.

Growing community of inventors

Pittsford, NY, United States of America

Alexander Shustorovich