Abbyy Development Inc.

Abbyy Production LLC

Abbyy Software Limited

Andrey Anatolievich Isaev

Vasily Vladimirovich Panferov

Ivan Khintsitskiy

Catherine Yurievna Bobrova

Olga Zhukovskaya

Konstantin Anisimovich

Dmitry Deryagin

Sergey Fedorov

Anatoly Smirnov

Anton Andreevich Masalovich

A data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a data field. One or more text regions in a selected frame of the plurality of frames are identified. One of the one or more identified text regions that corresponds to a set of attributes associated with the data field are selected. The data of the one of the one or more identified text regions of the selected frame are compared with data of one or more text regions of a subsequent frame. Responsive to determining that the data of the one or more text regions of the subsequent frame is a closer match to the set of attributes, the data of the one of the one or more identified text regions of the selected frame are updated. The data of the one of the one or more identified text regions is then provided to a client device.

Video capture in data capture scenario

A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation with the frame in a user interface.

Systems and methods for finding and presenting differences between documents are provided. One method includes identifying one or more differences between a first document and at least one second document. The method further includes determining each of the one or more differences to be either a significant difference or an insignificant difference. The method further includes providing a first identification of the significant differences and a second identification of the insignificant differences.

Method and apparatus for finding differences in documents

Systems and methods for enhancing and comparing documents. An example method comprises: comparing document images to identify a first document image of a reference document that corresponds with a second document image of a related document; transforming the second document image based on a layout of the first document image; and performing character recognition of the second document image.

Comparing documents using a trusted source

Disclosed are systems, methods and computer program products for using prior frame data for OCR processing of frames in video sources to detect natural language text therein. An example includes receiving a frame from a video source and retrieving prior frame data associated with the video source. The OCR-processing includes using prior frame data to detect blobs similar to blobs described in the prior frame data; using detected similar blobs to detect in the frame character candidates similar to character candidates described in the prior frame data; using detected similar character candidates to detect in the frame text candidates similar to text candidates described in the prior frame data; and using detected similar text candidates to detect in the frame text strings similar to text strings described in the prior frame data.

System and method for using prior frame data for OCR processing of frames in video sources

For extracting data from a document with fixed structure, we recognize key words in an image of the document; identify reference object based on these key words, create templates based on the identified reference objects; match the created templates against the image of the document while recognizing fields in the image of the document these templates; and select the best template using quality of the recognized field.

Data capture from images of documents with fixed structure

Systems and methods for finding and presenting differences between documents are provided. One method includes identifying one or more differences between a first document and at least one second document. The method further includes determining each of the one or more differences to be either a significant difference or an insignificant difference. The determination of whether each of the one or more differences is a significant difference or an insignificant difference may be performed in an automated manner without intervention from a user. The method further includes providing an identification of the significant differences to the user. The method further includes either hiding the insignificant differences from the user or providing an identification of the insignificant differences in a different manner than a manner in which the identification of the significant differences is provided.

A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation in a user interface.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying one or more document images based on its content by determining blocks layout of the document image; recognizing the document image to obtain digital content data representing text content or the potential graphical content of the image; calculating feature values of the document image for features based on the digital content data and the blocks layout; and classifying the document image as belonging to one of document classes based on the calculated feature values.

Content-based document image classification

Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Scanning device having a bed cover including a pattern of repeated design elements

A method for recognizing characters in an image includes receiving the image containing characters to be recognized and analyzing the received image. A first portion of the received image is compared to a set of patterns to determine a first coincidence value for each pattern in the set of patterns and a first series of hypotheses is generated based at least on the determined first coincidence values. A second portion of the received image is compared to a set of selected patterns to determine a second coincidence value for each pattern in the set of selected patterns, where the set of selected patterns is selected based at least on the generated first series of hypotheses. Recognition of the characters is based on the first and second series of hypotheses, and an identified sequence of characters.

Incomplete patterns

Document scanning method, system, and device having sets of parallel lines as background

Scanning implemented software for time economy without rescanning (S.I.S.T.E.R.) identifying multiple documents with first scanning pass and generating multiple images with second scanning pass

Methods and system for processing document images in OCR systems, particularly for selecting a proper file name for a recognized document. The method comprises generating at least one document type hypothesis for the document; verifying each document type hypothesis; selecting a best document type hypothesis and saving the document with a proper name based on the best type hypothesis and unique features. The method further includes determining a logical structure of a document and selecting a best document model hypothesis that has the best degree of correspondence with the selected best block hypotheses for the document. On the basis of the best document model hypothesis the text document reflecting the logical structure of the source document in extended computer-editable format is formed and saved with a proper file name.

Growing community of inventors

Moscow, Russia

Andrey Anatolievich Isaev