Abbyy Development Inc.

Ivan Khintsitskiy

Andrey Anatolievich Isaev

Ivan Germanovich Zagaynov

Stepan Yurievich Lobastov

Juri Katkov

Vasily Shahov

Olga Titova

Sergey Fedorov

Anton Andreevich Masalovich

A computer-implemented method for image capture by a mobile device, comprising: receiving, by a video capturing application running on a mobile device, a video stream from a camera of the mobile device; identifying a specific frame of the video stream; generating a plurality of hypotheses defining image borders within the specific frame; selecting, by a neural network, a particular hypothesis among the plurality of hypotheses; producing a candidate image by applying the particular hypothesis to the specific frame; determining a value of a quality metric of the candidate image; determining that the value of the quality metric of the candidate image exceeds one or more values of the quality metric of one or more previously processed images extracted from the video stream; wherein the image capture application is a zero-footprint application.

Zero-footprint image capture by mobile device

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

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.

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Moscow, Russia

Ivan Khintsitskiy