Patents by Inventor Vladimir Rybkin

Vladimir Rybkin has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11157779
    Abstract: A classification engine generates, using a weighted graph, a plurality of sets of confused graphemes based on recognition data for a plurality of document images; receives an input grapheme image associated with a document image comprising a plurality of grapheme images; determines a set of recognition options for the input grapheme image, where the set of recognition options comprises a set of target characters that are similar to the input grapheme image; identifies a neural network trained to recognize a first set of confused graphemes, where the first set of confused graphemes comprises at least a portion of the set of recognition options for the input grapheme image; and determines a grapheme class for the input grapheme image using the identified neural network.
    Type: Grant
    Filed: February 14, 2020
    Date of Patent: October 26, 2021
    Assignee: ABBYY Production LLC
    Inventors: Aleksey Alekseevich Zhuravlev, Vladimir Rybkin, Konstantin Vladimirovich Anisimovich, Azat Aydarovich Davletshin
  • Patent number: 10726557
    Abstract: The current document is directed to methods and systems that acquire an image containing text with curved text lines to generate a corresponding corrected image in which the text lines are straightened and have a rectilinear organization. The method may include identifying a page sub-image within the text-containing image, generating a text-line-curvature model for the page sub-image that associates inclination angles with pixels in the page sub-image, generating local displacements, using the text-line-curvature model, for pixels in the page sub-image, and transferring pixels from the page sub-image to a corrected page-sub-image using the local displacements to construct a corrected page sub-image in which the text lines are straightened and in which the text characters and symbols have a rectilinear arrangement.
    Type: Grant
    Filed: September 30, 2019
    Date of Patent: July 28, 2020
    Assignee: ABBYY Production LLC
    Inventors: Olga Arnoldova Kacher, Ivan Germanovich Zagaynov, Vladimir Rybkin
  • Publication number: 20200184280
    Abstract: A classification engine generates, using a weighted graph, a plurality of sets of confused graphemes based on recognition data for a plurality of document images; receives an input grapheme image associated with a document image comprising a plurality of grapheme images; determines a set of recognition options for the input grapheme image, where the set of recognition options comprises a set of target characters that are similar to the input grapheme image; identifies a neural network trained to recognize a first set of confused graphemes, where the first set of confused graphemes comprises at least a portion of the set of recognition options for the input grapheme image; and determines a grapheme class for the input grapheme image using the identified neural network.
    Type: Application
    Filed: February 14, 2020
    Publication date: June 11, 2020
    Inventors: Zhuravlev Aleskey Alekseevich, Vladimir Rybkin, Anisimovich Konstantin Vladimirovich, Davletshin Azat Aydarovich
  • Patent number: 10565478
    Abstract: A classification engine stores a plurality of neural networks in memory, where each neural network is trained to recognize a set of confused graphemes from one or more sets of confused graphemes identified in recognition data for a plurality of document images. The classification engine receives an input grapheme image associated with a document image comprising a plurality of graphemes, determines a set of recognition options for the input grapheme image, wherein the set of recognition options comprises a set of target characters that are similar to the input grapheme image, selects a first neural network from the plurality of neural networks, wherein the first neural network is trained to recognize a first set of confused graphemes, and wherein the first set of graphemes comprises at least a portion of the set of recognition options for the input grapheme image, and determines a grapheme class for the input grapheme image using the selected first neural network.
    Type: Grant
    Filed: June 16, 2017
    Date of Patent: February 18, 2020
    Assignee: ABBYY PRODUCTION LLC
    Inventors: Zhuravlev Aleskey Alekseevich, Vladimir Rybkin, Anisimovich Konstantin Vladimirovich, Davletshin Azat Aydarovich
  • Publication number: 20200034973
    Abstract: The current document is directed to methods and systems that acquire an image containing text with curved text lines to generate a corresponding corrected image in which the text lines are straightened and have a rectilinear organization. The method may include identifying a page sub-image within the text-containing image, generating a text-line-curvature model for the page sub-image that associates inclination angles with pixels in the page sub-image, generating local displacements, using the text-line-curvature model, for pixels in the page sub-image, and transferring pixels from the page sub-image to a corrected page-sub-image using the local displacements to construct a corrected page sub-image in which the text lines are straightened and in which the text characters and symbols have a rectilinear arrangement.
    Type: Application
    Filed: September 30, 2019
    Publication date: January 30, 2020
    Inventors: Olga Arnoldova Kacher, Ivan Germanovich Zagaynov, Vladimir Rybkin
  • Patent number: 10430948
    Abstract: The current document is directed to methods and systems that straighten in the text lines of text-containing digital images. Initial processing of a text-containing image identifies the outline of a text-containing page. Next, aggregations of symbols, including words and word fragments, are identified within the outlined page image. The centroids and inclination angles of the symbol aggregations are determined, allowing each symbol aggregation to be circumscribed by a closest-fitting rectangle oriented in conformance with the inclination angle determined for the circumscribed symbol aggregation. A model is constructed for the text-line curvature within the text image based on the circumscribed symbol aggregations and is refined using additional information extracted from the text image. The model, essentially an inclination-angle map, allows for assigning local displacements to pixels within the page image which are then used to straighten the text lines in the text image.
    Type: Grant
    Filed: August 16, 2016
    Date of Patent: October 1, 2019
    Assignee: ABBYY PRODUCTION LLC
    Inventors: Olga Arnoldovna Kacher, Ivan Germanovich Zagaynov, Vladimir Rybkin
  • Patent number: 10366469
    Abstract: The current document is directed to methods and systems that straighten curvature in the text lines of text-containing digital images, including text-containing digital images generated from the two pages of an open book. Initial processing of a text-containing image identifies the outline of a text-containing page. Next, contours are generated to represent each text line. The midpoints and inclination angles of the links or vectors that comprise the contour lines are determined. A model is constructed for the perspective-induced curvature within the text image. In one implementation, the model, essentially an inclination-angle map, allows for assigning local displacements to pixels within the page image which are then used to straighten the text lines in the text image. In another implementation, the model is essentially a pixel-displacement map which is used to straighten the text lines in the text image.
    Type: Grant
    Filed: December 13, 2016
    Date of Patent: July 30, 2019
    Assignee: ABBYY PRODUCTION LLC
    Inventors: Ivan Zagaynov, Vladimir Rybkin
  • Publication number: 20190180154
    Abstract: A method includes obtaining an image of text. The text in the image includes one or more words in one or more sentences. The method also includes providing the image of the text as first input to a set of trained machine learning models, obtaining one or more final outputs from the set of trained machine learning models, and extracting, from the one or more final outputs, one or more predicted sentences from the text in the image. Each of the one or more predicted sentences includes a probable sequence of words.
    Type: Application
    Filed: December 20, 2017
    Publication date: June 13, 2019
    Inventors: Nikita Orlov, Vladimir Rybkin, Konstantin Anisimovich, Azat Davletshin
  • Patent number: 10200448
    Abstract: An original image of a physical document is received by a client device, a reduced file containing data indicative of a document type is created based on the original image that is substantially smaller in size than the original image. The client device sends a request including the reduced file to a server for information pertaining to a document type for the physical document, receives location information based on the document type from the server for at least one portion of the original image that contains at least one content item for the physical document, and extracts the at least one portion of the original image based on the location information to generate at least one extracted portion of the image. The client device sends a second request including the at least one extracted portion of the image to the server for the at least one content item. Responsive to receiving the at least one content item from the server device, the client device provides the at least one content item for display.
    Type: Grant
    Filed: December 14, 2016
    Date of Patent: February 5, 2019
    Assignee: ABBYY DEVELOPMENT LLC
    Inventor: Vladimir Rybkin
  • Publication number: 20180349742
    Abstract: A classification engine stores a plurality of neural networks in memory, where each neural network is trained to recognize a set of confused graphemes from one or more sets of confused graphemes identified in recognition data for a plurality of document images. The classification engine receives an input grapheme image associated with a document image comprising a plurality of graphemes, determines a set of recognition options for the input grapheme image, wherein the set of recognition options comprises a set of target characters that are similar to the input grapheme image, selects a first neural network from the plurality of neural networks, wherein the first neural network is trained to recognize a first set of confused graphemes, and wherein the first set of graphemes comprises at least a portion of the set of recognition options for the input grapheme image, and determines a grapheme class for the input grapheme image using the selected first neural network.
    Type: Application
    Filed: June 16, 2017
    Publication date: December 6, 2018
    Inventors: Zhuravlev Aleskey Alekseevich, Vladimir Rybkin, Anisimovich Konstantin Vladimirovich, Davletshin Azat Aydarovich
  • Publication number: 20180167440
    Abstract: An original image of a physical document is received by a client device, a reduced file containing data indicative of a document type is created based on the original image that is substantially smaller in size than the original image. The client device sends a request including the reduced file to a server for information pertaining to a document type for the physical document, receives location information based on the document type from the server for at least one portion of the original image that contains at least one content item for the physical document, and extracts the at least one portion of the original image based on the location information to generate at least one extracted portion of the image. The client device sends a second request including the at least one extracted portion of the image to the server for the at least one content item. Responsive to receiving the at least one content item from the server device, the client device provides the at least one content item for display.
    Type: Application
    Filed: December 14, 2016
    Publication date: June 14, 2018
    Inventor: Vladimir Rybkin
  • Publication number: 20180018774
    Abstract: The current document is directed to methods and systems that straighten in the text lines of text-containing digital images. Initial processing of a text-containing image identifies the outline of a text-containing page. Next, aggregations of symbols, including words and word fragments, are identified within the outlined page image. The centroids and inclination angles of the symbol aggregations are determined, allowing each symbol aggregation to be circumscribed by a closest-fitting rectangle oriented in conformance with the inclination angle determined for the circumscribed symbol aggregation. A model is constructed for the text-line curvature within the text image based on the circumscribed symbol aggregations and is refined using additional information extracted from the text image. The model, essentially an inclination-angle map, allows for assigning local displacements to pixels within the page image which are then used to straighten the text lines in the text image.
    Type: Application
    Filed: August 16, 2016
    Publication date: January 18, 2018
    Inventors: Olga Arnoldovna Kacher, Ivan Germanovich Zagaynov, Vladimir Rybkin
  • Publication number: 20170372460
    Abstract: The current document is directed to methods and systems that straighten curvature in the text lines of text-containing digital images, including text-containing digital images generated from the two pages of an open book. Initial processing of a text-containing image identifies the outline of a text-containing page. Next, contours are generated to represent each text line. The midpoints and inclination angles of the links or vectors that comprise the contour lines are determined. A model is constructed for the perspective-induced curvature within the text image. In one implementation, the model, essentially an inclination-angle map, allows for assigning local displacements to pixels within the page image which are then used to straighten the text lines in the text image. In another implementation, the model is essentially a pixel-displacement map which is used to straighten the text lines in the text image.
    Type: Application
    Filed: December 13, 2016
    Publication date: December 28, 2017
    Inventors: Ivan Zagaynov, Vladimir Rybkin
  • Patent number: 9477898
    Abstract: Methods for correcting distortions in an image including text, or an image of a page that includes text, are disclosed. The methods include identifying reliable and substantially straight lines from elements in the image. Vanishing points are determined from the lines. Parameters associated with a rectangle are determined. A coordinate conversion is performed.
    Type: Grant
    Filed: June 26, 2014
    Date of Patent: October 25, 2016
    Assignee: ABBYY Development LLC
    Inventors: Olga Kacher, Vladimir Rybkin
  • Patent number: 8885972
    Abstract: Methods for correcting distortions in an image including text, or an image of a page that includes text, are disclosed. The methods include identifying reliable and substantially straight lines from elements in the image. Vanishing points are determined from the lines. Parameters associated with a rectangle are determined. A coordinate conversion is performed.
    Type: Grant
    Filed: July 30, 2012
    Date of Patent: November 11, 2014
    Assignee: ABBYY Development LLC
    Inventors: Olga Kacher, Vladimir Rybkin
  • Publication number: 20140307967
    Abstract: Methods for correcting distortions in an image including text, or an image of a page that includes text, are disclosed. The methods include identifying reliable and substantially straight lines from elements in the image. Vanishing points are determined from the lines. Parameters associated with a rectangle are determined. A coordinate conversion is performed.
    Type: Application
    Filed: June 26, 2014
    Publication date: October 16, 2014
    Applicant: ABBYY Development LLC
    Inventors: Olga Kacher, Vladimir Rybkin
  • Patent number: 8606015
    Abstract: Disclosed is a method of bit-mapped image analysis that comprises a whole image data representation via its component objects. The objects are assigned to different levels of complexity. The objects may be hierarchically connected by spatially-parametrical links. The method comprises preliminarily generating a classifier of image objects consisting of one or more levels differing in complexity; parsing the image into objects; attaching each object to one or more predetermined levels; establishing hierarchical links between objects of different levels; establishing links between objects within the same level; and performing an object feature analysis. Object feature analysis comprises generating and examining a hypothesis about object features and correcting the concerned object's features of the same and other levels in response to results of hypothesis examination. Object feature analysis may also comprise execution of a recursive X-Y cut within the same level.
    Type: Grant
    Filed: December 21, 2011
    Date of Patent: December 10, 2013
    Assignee: ABBYY Development LLC
    Inventors: Konstantin Anisimovich, Dmitry Deryagin, Vladimir Rybkin
  • Patent number: 8379119
    Abstract: Embodiments of the present invention disclose a method, device and system for restoring a motion-blurred image. The method comprises determining parameters for a one-dimensional Optical Transfer Function (OTF) for the motion-blurred image in Fourier space; determining a signal-to-noise ratio for the motion-blurred image in the Fourier space; and correcting for motion blur based on the parameters of the OTF. Determining the parameters comprises calculating a function ?(p,q) which is based on the square of the modulus of the Fourier transform |G(p,q)|2 of the motion-blurred image. The parameters include the absolute value of the one-dimensional OTF, and the phase and sign of the OTF.
    Type: Grant
    Filed: September 23, 2011
    Date of Patent: February 19, 2013
    Assignee: ABBYY Software Ltd.
    Inventors: Vladimir Rybkin, Sergey Fedorov
  • Publication number: 20120321216
    Abstract: Methods for correcting distortions in an image including text, or an image of a page that includes text, are disclosed. The methods include identifying reliable and substantially straight lines from elements in the image. Vanishing points are determined from the lines. Parameters associated with a rectangle are determined. A coordinate conversion is performed.
    Type: Application
    Filed: July 30, 2012
    Publication date: December 20, 2012
    Applicant: ABBYY SOFTWARE LTD.
    Inventors: Olga Kacher, Vladimir Rybkin
  • Publication number: 20120237135
    Abstract: Embodiments of the present invention disclose a method, device and system for restoring a motion-blurred image. The method comprises determining parameters for a one-dimensional Optical Transfer Function (OTF) for the motion-blurred image in Fourier space; determining a signal-to-noise ratio for the motion-blurred image in the Fourier space; and correcting for motion blur based on the parameters of the OTF. Determining the parameters comprises calculating a function ?(p,q) which is based on the square of the modulus of the Fourier transform |G(p,q)|2 of the motion-blurred image. The parameters include the absolute value of the one-dimensional OTF, and the phase and sign of the OTF.
    Type: Application
    Filed: September 23, 2011
    Publication date: September 20, 2012
    Inventors: Vladimir Rybkin, Sergey Fedorov