Abstract: According to an aspect of an embodiment, an apparatus for analyzing and determining correlation of information contained in a given form containing blocks, at least one of the blocks containing data indicative of a header, the rest of the blocks containing data in association with header information, comprising: a memory for storing templates having nodes, character data associated with said nodes respectively, and relative position information between said nodes; and a processor for analyzing and determining correlation of the information according to a process comprising: obtaining data contained in said blocks in the given form, determining relative position of said blocks to produce relative position information, analyzing the data obtained from the blocks and the relative position information of the blocks in comparison with the character data and the relative position information of said nodes of said templates, and determining correlation of the data contained in said blocks.

Abstract: This invention provides a correcting device and a correcting method for perspective transformation of document images.

Abstract: A form processing program which is capable of automatically extracting keywords. When the image of a scanned form is entered, a layout recognizer extracts a readout region of the form image, a character recognizer recognizes characters within the readout region. A form logical definition database stores form logical definitions defining strings as keywords according to logical structures which are common to forms of same type. A possible string extractor extracts as possible strings combinations of recognized characters each of which satisfies defined relationships of a string. A linking unit links the possible strings according to positional relationships, and determines a combination of possible strings as keywords.

Abstract: A character area extracting device includes a reflective and non-reflective area separation unit separating image data into reflective and non-reflective areas, and binarizing the image data by changing a first threshold value when it is inappropriate; a reflective area binarizing unit separating the reflective area into character and background areas, and binarizing it by changing a second threshold value when it is inappropriate; a non-reflective area binarizing unit separating the non-reflective area into the character and background areas, and binarizing it by changing a third threshold value when it is inappropriate; a reflective and non-reflective area separation evaluation unit; and a line extracting unit connecting the character areas of the reflective and non-reflective areas and extracting positional information of the connected character areas in the image data.

Abstract: A document recognizing apparatus includes a display control unit which displays a document data including a character string related to a character string selected by a user, and an area that includes at least a character string of the document data.

Abstract: A set of straight lines that associate a top parallel geodesic projection positioned at an upper end with a bottom parallel geodesic projection positioned at a lower end, among sets of parallel geodesic projections, is extracted as a set of ruled-line candidate projections as a search target of a set of ruled line projections. A deviation of neighborhood, which is a distance between a cross ratio vector of the ruled-line candidate projection and a cross ratio vector of a neighboring line obtained by shifting the ruled-line candidate projection by a predetermined interval, is calculated for each ruled-line candidate projection. A set of straight lines having the smallest sum total of deviations of neighborhood, in the set of straight lines, which do not intersect with each other, among the sets of ruled-line projection candidates is extracted as a set of ruled line projections by continuous dynamic programming.

Abstract: A form processing apparatus extracts layout information and character information from a form document. A candidate extracting unit extracts word candidates from the character information. A frequency digitizing unit calculates emission probability of a word candidate from each element. A relation digitizing unit calculates transition probability that relationship between word candidates is established. An evaluating unit calculates an evaluation value indicative of a probability of appearance of word candidates in respective logical elements. A determining unit determines the element and a word candidate thereof as the element and a character string thereof in the form document, based on the evaluation value.

Abstract: A ruled line extracting apparatus, a ruled line extracting program and a ruled line extracting method re-extract a ruled line by changing the predetermined requirements to be met by ruled line s when a ruled line candidate extracted according to the requirements shows a low reliability.

Abstract: A layout analysis program, a layout analysis apparatus, layout analysis method and a medium can highly accurately extract a text block from an image if the image is a color image.

Abstract: A document type identifying apparatus includes in advance a database storing therein keywords used as keys that identify document types in association with each document type. The document type identifying apparatus aligns word strings written on a document and generates partial keyword strings for each keyword by using the keywords stored in the database. The partial keyword strings are to be checked for matching with the word strings written on the document. Then, the document type identifying apparatus checks matching of the grouped and aligned word strings with the partial keyword strings and obtains, for each keyword, each number of matched words with the highest matching rates between the grouped word strings that are successfully matched and the partial keyword strings. Then, each number of matched words is used to calculate each evaluation value to determine the document type.

Abstract: A document layout analysis program capable of extracting an appropriate set of text blocks from a given document image even in the case where the document layout is so complicated that conventional extraction methods with a single extraction condition would not work well. A plurality of different extraction conditions are stored in an extraction condition memory for use in extracting text blocks from a given document image. In accordance with those extraction conditions, a text block extractor extracts a plurality of sets of text blocks from the document image. A text block consolidator produces a consolidated set of text blocks by performing character recognition on each extracted text block, evaluating validity of each text block based on a result of the character recognition, and selecting most valid text blocks from among the plurality of sets of text blocks.

Abstract: A program causes a computer to function as a document recognition apparatus, having an extraction unit for extracting connected components of pixels from an input image, a generation unit for generating a reference element that is connected components of pixels extracted by the extraction unit and combined elements obtained by combining the reference element and connected components of pixels adjacent to the reference element as an element to be estimated, a calculation unit for calculating a degree of certainty that indicates how much the element to be estimated generated by the generation unit seems to be a character, and a determination unit for identifying elements that seem to be characters among the elements to be estimated based on the degree of certainty calculated by the calculation unit.

Abstract: An area extraction method including obtaining a character lattice showing a connection relation between unit areas, which are obtained by separating a character string pattern in an image into patterns each recognized as corresponding to a single character, judging whether or not all combinations of each of the unit areas in the obtained character lattice and each of the unit areas in a regular lattice defining a regular connection relation between the unit areas are likely to be established, generating a path coupling between nodes corresponding to the combination of the unit areas which is determined as likely to be established, determining an optimum path from the generated paths based on a degree of coincidence with the regular lattice or the character lattice, and extracting from an image the unit areas in the character lattice corresponding to the determined optimum path.

Abstract: A method for assisting in the creation of a logical structure model, which stores, from an image in which character strings associated respectively with a plurality of logical elements constituting a logical structure are described, the logical elements, character strings associated with the logical elements, and the logical structure, wherein character strings in an input image and the logical structure among the character strings in the input image are extracted, a logical element is selected among the plurality of logical elements according to the degrees of similarity between the extracted character strings and the character string associated respectively with the plurality of logical elements stored in the logical structure model, a character string associated with the selected logical element and a character string in the input image associated with the logical element based on the logical structure among the extracted character strings in the input image are extracted.

Abstract: A document recognizing apparatus includes a display control unit which displays a document data including a character string related to a character string selected by a user, and an area that includes at least a character string of the document data.

Abstract: The form data extracting apparatus, even input form does not have a logical structure stored in the generic logical structure DB, by using logical elements in the existing logical structure and a registered form obtained on the basis of (a) the logical structure, (b) pieces of position information of the logical elements, and (c) a relation between the logical elements. A logical element and a logical structure are extracted from the input form, and the extracted logical structure can be defined as a new registered form or a new logical structure.

Abstract: An image recognition apparatus recognizes the correspondence between character strings and logical elements composing a logical structure in an image in which the character strings are described as the logical elements to recognize each logical element.

Abstract: An image recognition method is conducted by recognizing logical elements based on a logical structure model set to correspond to the logical structure of an image of individual character strings, collecting information processed with the logical structure model of images of a logical structure, acquiring a recognition result when recognizing an image of a logical structure by processing information collected with a post-update logical structure model, and outputting warning information about the post-update logical structure model to an output unit when a result of the comparison is a non-match.

Abstract: A character recognition apparatus includes a hash table registering unit and a recognition processing unit. The hash table registering unit creates a hash table indicating a characteristic of each of partial character images as an area of each character. The recognition processing unit divides an input image into partial input images, and calculates a characteristic of each partial input image. The recognition processing unit searches the hash table for a partial character image having a characteristic similar to that of each partial input image. The recognition processing unit compares a positional relationship of the partial input images with that of the partial character images to determine whether they match, and recognizes a character in each area of the input image.

Abstract: A projection set of geodesic lines which are parallel with each other on a curved surface of a paper face is extracted from an image in which a paper face has been imaged by an image-pickup device, using the paper face contents as a clue; and also a projection set of ruling lines which form a ruled surface corresponding to the curved surface of the paper face is extracted from the projection set of geodesic lines. Then, the curved surface of the paper face is estimated from the projection set of the geodesic lines and ruling lines, and distortion of the image is corrected based on this curved surface of the paper face. If this is done, correspondence with various types of diverse distortions becomes possible, and distortion correction can be performed even when only one part of the paper face appears in the image.