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: A method for correcting distortions in a scanned image of a page, paragraph, sentence or other portion of text is disclosed. The method comprises identifying at least one set of collinear elements in the scanned image; and generating a corrected image based on the scanned image including for at least some of the collinear elements in each set applying a spatial location correction to position all collinear elements in the set on a common horizontal rectilinear base line in the corrected image.

Abstract: In one embodiment, a method for correcting distortions in a scanned image of a page is disclosed. The method comprises identifying at least one set of collinear elements in the scanned image; and generating a corrected image based on the scanned image including for at least some of the collinear elements in each set applying a spatial location correction to position all collinear elements in the set on a common horizontal rectilinear base line in the corrected image.

Abstract: The present invention discloses a multilevel method of bitmapped image analysis that comprises a whole image data representation via its components—objects of different levels of complexity—hierarchically connected therebetween by spatially-parametrical links. The said method comprises preliminarily generating a classifier of the objects that possibly may be present in the image consisting of one or more levels differing in complexity; parsing the image into objects; attaching each object to one of predetermined levels; establishing hierarchical links between objects of different levels; establishing links between objects within the same level; and performing an object feature analysis. The objects feature analysis comprises at least generating and examining a hypothesis about object features and correcting the object's features of the same and other levels in response to the hypothesis examination results.

Abstract: Embodiments of the present invention disclose a method 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.

Abstract: The present invention discloses a multilevel method of bit-mapped image analysis that comprises a whole image data representation via its components—objects of different levels of complexity—hierarchically connected therebetween by spatially-parametrical links. The said method comprises preliminarily generating a classifier of the objects that possibly may be present in the image consisting of one or more levels differing in complexity; parsing the image into objects; attaching each object to one of predetermined levels; establishing hierarchical links between objects of different levels; establishing links between objects within the same level; performing an objects features analysis. The objects feature analysis comprises at least generating and examining a hypothesis about object features and correcting the concerned objects' features of the same and other levels in response to the hypothesis examination results.

Abstract: The present invention discloses a method of character and text recognition of a bit-mapped graphic file received from an optical scanning device. The method comprises a trainable template cache, a preliminarily trained feature analysis means, and a context analysis means. The present invention discloses the way to use said means for achieving the best results in recognition. The method supposes that the template cache along with the context analysis means are used as the main shape characteristic analyzing means. The feature analysis means along with the context analysis means are used as subsidiary shape characteristic analyzing means and as a training means for the template cache. The method comprises applying the main shape characteristic analyzing means and optionally applying the subsidiary shape characteristic analyzing means if no or not enough reliability of recognition is achieved after the template cache analyzing.

Abstract: Embodiments of the present invention disclose a method 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.

Abstract: The present invention deals with text comprising image parsed to graphemes. A result of character recognition is creation of one or more versions of characters for each grapheme. All possible words versions are obtained using all characters versions, and all parsing versions are examined. A supplementary data of several types is applied successively in the preliminarily prescribed order to the examined words. The processing with the use of supplemental data may be represented as a three times repeated processing of the same text fragment with the use of supplementary information becoming available at each time. The examination comprises three steps. 1) A set of chains LPG is built using all obtained recognized grapheme-to-character versions. 2) All obtained versions are analyzed with the successive application of subsequent supplemental data types in connection with the preliminarily assigned order or with a joint application thereof. 3) A supplementary space recognition correction.

Abstract: In one embodiment, a method for correcting distortions in a scanned image of a page is disclosed. The method comprises identifying at least one set of collinear elements in the scanned image; and generating a corrected image based on the scanned image including for at least some of the collinear elements in each set applying a spatial location correction to position all collinear elements in the set on a common horizontal rectilinear base line in the corrected image.

Abstract: The present invention deals with text comprising image parsed to graphemes. A result of character recognition is creation of one or more versions of characters for each grapheme. All possible words versions are obtained using all characters versions, and all parsing versions are examined. A supplementary data of several types is applied successively in the preliminarily prescribed order to the examined words. The processing with the use of supplemental data may be represented as a three times repeated processing of the same text fragment with the use of supplementary information becoming available at each time. The examination comprises three steps. 1) A set of chains LPG is built using all obtained recognized grapheme-to-character versions. 2) All obtained versions are analyzed with the successive application of subsequent supplemental data types in connection with the preliminarily assigned order or with a joint application thereof. 3) A supplementary space recognition correction.

Abstract: A method is described of bit-mapped image analysis comprising division of all analysis means at one's disposal into several groups differing in accuracy and further processing multi-stage analysis. The analysis comprises a primary analysis stage and at least one profound analysis stage, with supplemental data collected at both stages. The primary analysis, includes preliminary recognition of objects with distortion and detection of objects that require more precise analysis means to overcome the distortion. At the primary analysis stage, the analysis means from the group of the most inaccurate group are used. The profound analysis stage includes repeating recognition of objects with a distortion taking into account the supplemental data obtained at the previous stage, detecting objects that require more precise analysis means to overcome the distortion, and collection of newly appeared supplemental data. Each subsequent profound analysis stage uses analysis means from the group of more accurate means.

Abstract: A method is described of bit-mapped image analysis comprising division of all analysis means at one's disposal into several groups differing in accuracy and further processing multi-stage analysis.

Abstract: The present invention discloses a method of character and text recognition. A method supposes that feature analysis means along with context analysis means are used as subsidiary shape characteristic analyzing means and as a training means for template cache.

Abstract: The disclosed invention utilizes a complex estimation-based approach to identify languages of portions of a multi-lingual text, recognized from a bit-mapped image. The method comprises besides the traditional steps like the document segmentation, new ones such as generating and testing of a hypothesis about the characters in the word tokens.