Abstract: Systems and methods are disclosed to receive an image depicting at least a part of a document and identify a plurality of partition points dividing the image into potential segments; generate a linear partition graph (LPG) comprising a plurality of vertices using the plurality of partition points and a plurality of arcs connecting the plurality of vertices; identify a path of the LPG having a value of a quality metric above a threshold value, wherein the path is selected from a plurality of paths of the LPG and comprises one or more arcs and the value of the quality metric is derived using a neural network classifying each of a plurality of pixels of the image; and generate one or more blocks of the image wherein each of the one or more blocks corresponds to an arc of the identified path and represents a portion of the image associated with a type of an object.

Abstract: Systems and methods are disclosed to receive an image depicting at least a part of a document and identify a plurality of partition points dividing the image into potential segments; generate a linear partition graph (LPG) comprising a plurality of vertices using the plurality of partition points and a plurality of arcs connecting the plurality of vertices; identify a path of the LPG having a value of a quality metric above a threshold value, wherein the path is selected from a plurality of paths of the LPG and comprises one or more arcs and the value of the quality metric is derived using a neural network classifying each of a plurality of pixels of the image; and generate one or more blocks of the image wherein each of the one or more blocks corresponds to an arc of the identified path and represents a portion of the image associated with a type of an object.

Abstract: Systems and methods for identifying screenshots within document images. An example method comprises: receiving an image of at least a part of a document; identifying, within the image, a polygonal object having a visually distinct border comprising a plurality of edges of one or more intersecting rectangles; asserting a screenshot image hypothesis with respect to the identified polygonal object; and responsive to evaluating at least one condition associated with one or more attributes of the identified polygonal object, classifying the identified polygonal object as a screenshot image.

Abstract: The current application is directed to a method and system for automatically determining the sense orientation of regions of scanned-document images. In one implementation, the sense-orientation method and system to which the current application is directed employs a relatively small set of orientation characters that occur frequently in printed text. In this implementation, for at least one set of orientation characters, each of two or more different orientations of character-containing subregions within a text-containing region of a scanned-document image are compared to each orientation character in the at least one set of orientation characters in order to determine an orientation for each of the character-containing subregions with respect to a reference orientation of the text-containing region. The determined orientations for the character-containing subregions are then used to determine an overall sense orientation for the text-containing region of the scanned-document image.

Abstract: Systems and methods for identifying screenshots within document images. An example method comprises: receiving an image of at least a part of a document; identifying, within the image, a polygonal object having a visually distinct border comprising a plurality of edges of one or more intersecting rectangles; asserting a screenshot image hypothesis with respect to the identified polygonal object; and responsive to evaluating at least one condition associated with one or more attributes of the identified polygonal object, classifying the identified polygonal object as a screenshot image.

Abstract: The current document is directed to methods and systems that classify electronic documents. In one implementation, multiple hypotheses for the type and structure of the document are automatically generated or identified. A page hypothesis is selected for each page of the document, using one or more page hypotheses already selected for one or more neighboring pages when such already selected page hypotheses are available. The selected page hypotheses are then used to automatically select one of the multiple document hypotheses and a corresponding document type, following which various document-processing and document-refinement operations can be applied to the document according to the selected document hypothesis and document type.

Abstract: In one embodiment, a method for identifying areas in a document image is provided. The method comprises generating binarized and gradient images based on the document image; and performing a classification operation to classify areas in the document image into one of a noise area and a picture area based on attributes computed on the binarized and gradient images.

Abstract: The invention relates to methods for determining a logical structure of a document. The system stores a collection of models, each of which describes one or more possible logical structures. At least one document hypothesis is generated for the whole document. For each document hypothesis, the system verifies the document hypothesis on each page, for example, by generating at least one block hypothesis for each block in the document based on the document hypothesis, selecting a best block hypothesis for each block, selecting the model that corresponds to a best document hypothesis the document hypothesis that has a best degree of correspondence with the selected best block hypotheses for the document, and forming a representation of the document based on the best document hypothesis described.

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.

Abstract: The invention relates to methods for determining a logical structure of a document. The system stores a collection of models, each of which describes one or more possible logical structures. At least one document hypothesis is generated for the whole document. For each document hypothesis, the system verifies the document hypothesis on each page, for example, by generating at least one block hypothesis for each block in the document based on the document hypothesis, selecting a best block hypothesis for each block, selecting the model that corresponds to a best document hypothesis the document hypothesis that has a best degree of correspondence with the selected best block hypotheses for the document, and forming a representation of the document based on the best document hypothesis described.

Abstract: 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.

Abstract: In one embodiment, the invention provides a method for determining a logical structure of a document. The method comprises generating at least one document hypothesis for the whole document; for each document hypothesis, verifying said document hypothesis including (a) generating at least one block hypothesis for each block in the document based on the document hypothesis; and (b) selecting a best block hypothesis for each block; selecting as a best document hypothesis the document hypothesis that has the best degree of correspondence with the selected best block hypotheses for the document; and forming the document based on the best document hypothesis.

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.

Abstract: In one embodiment, a method for identifying areas in a document image is provided. The method comprises generating binarized and gradient images based on the document image; and performing a classification operation to classify areas in the document image into one of a noise area and a picture area based on attributes computed on the binarized and gradient images.

Abstract: 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.

Abstract: In one embodiment, the invention provides a method for determining a logical structure of a document. The method comprises generating at least one document hypothesis for the whole document; for each document hypothesis, verifying said document hypothesis including (a) generating at least one block hypothesis for each block in the document based on the document hypothesis; and (b) selecting a best block hypothesis for each block; selecting as a best document hypothesis the document hypothesis that has the best degree of correspondence with the selected best block hypotheses for the document; and forming the document based on the best document hypothesis.