Abstract: A computation unit calculates luminance differences of individual pixel pairs in a feature area and calculates, based thereon, a local feature value formed from bit values respectively corresponding to the pixel pairs. Specifically, the computation unit calculates a specific luminance difference for a specific pixel pair corresponding to a specific bit value and then compares the result with a specified range including a zero point of luminance difference. Then a first value is assigned to the specific bit value when the specific luminance difference is greater than the upper bound of the specified range. A second value is assigned to the same when the specific luminance difference is smaller than the lower bound of the specified range. A predetermined one of the first and second values is assigned to the same when the specific luminance difference falls in the specified range.

Abstract: A memory stores area information indicating a pitcher area in which a pitcher is presumed to appear in an image that represents a pitching scene. A processor detects an edge pixel from a difference image that represents a difference between a first image at a first time and a second image at a second time that are included in a video, and identifies an edge area in which a plurality of edge pixels are aligned in a prescribed direction in the difference image. Then, the processor determines that the difference image represents the pitching scene on the basis of a size of the edge area included in the pitcher area indicated by the area information in the difference image and on the basis of a size of the edge area included in a prescribed area in the difference image.

Abstract: A color chart detection apparatus that detects a color chart from an image representing the color chart having a plurality of palettes arranged in a predefined order is provided. The color chart detection apparatus: extracts any pixel having a color component corresponding to each designated one of a predetermined number of palettes; selects at least three palettes to form a first group and, when a combination of pixels selected on a palette-by-palette basis from among the pixels extracted for the respective palettes included in the first group is arranged in the predefined order, detects each of the pixels included in the combination as being a candidate pixel; and based on the candidate pixel, computes color information representing color of the palette corresponding to the candidate pixel on the image and position information representing position of the corresponding palette on the image.

Abstract: A subject tracking device includes a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, detecting at least one subject candidate area in which it is probable that a tracking target subject appears on an image that is received from an imaging unit; calculating a degree of blur of the subject candidate area for each of the subject candidate areas; determining that the subject appears in a subject candidate area having a degree of blur in accordance with a moving speed of the subject, out of the subject candidate areas; and deciding movement of the subject depending on a movement direction from an area in which the subject appears on a previous image that is captured by the imaging unit before capturing the image, to the subject candidate area in which the subject appears on the image.

Abstract: An image processor includes: a memory; and a processor, wherein the processor is configured to: extract an arc area in an image captured by an image sensor; and determine whether a portion that protrudes from an arc in the arc area satisfies a first reference regarding a shape and detect the portion as a colony candidate when it is determined that the portion satisfies the first reference.

Abstract: A signal processing device includes: a memory; and a processor coupled to the memory and configured to: detect a second feature value relating to a first feature value recognized to satisfy a recognition condition, from a second time series prior to a first time series of the first feature value in a times series of a feature value corresponding to an input signal, and change the recognition condition so that the second feature value is recognized as a class for recognizing the first feature value.

Abstract: A color chart detection apparatus that detects a color chart from an image representing the color chart having a plurality of palettes arranged in a predefined order is provided. The color chart detection apparatus: extracts any pixel having a color component corresponding to each designated one of a predetermined number of palettes; selects at least three palettes to form a first group and, when a combination of pixels selected on a palette-by-palette basis from among the pixels extracted for the respective palettes included in the first group is arranged in the predefined order, detects each of the pixels included in the combination as being a candidate pixel; and based on the candidate pixel, computes color information representing color of the palette corresponding to the candidate pixel on the image and position information representing position of the corresponding palette on the image.

Abstract: A signal processing device includes: a memory; and a processor coupled to the memory and configured to: detect a second feature value relating to a first feature value recognized to satisfy a recognition condition, from a second time series prior to a first time series of the first feature value in a times series of a feature value corresponding to an input signal, and change the recognition condition so that the second feature value is recognized as a class for recognizing the first feature value.

Abstract: A signal processing device includes: a memory; and a processor coupled to the memory and configured to: detect a repetition of a feature value from a time series of the feature value corresponding to an input signal, change a recognition condition for recognizing a class for the feature value when the repetition of the feature value is detected.

Abstract: An information processing device includes a processor that executes a procedure. The procedure includes: (a) acquiring concentration level information relating to a degree of concentration of a user on the device; (b) acquiring action information that directly or indirectly represents an action of the user; (c) setting a first threshold that is for determining, in accordance with the concentration level information acquired in (a), whether or not the action information acquired in (b) is an operational instruction; and (d) determining, using the first threshold set in (c), whether or not the action of the user represented by the action information acquired in (b) is intended as an operational instruction by the user.

Abstract: A subject tracking device includes a processor; and a memory which stores a plurality of instructions, which when executed by the processor, cause the processor to execute, detecting at least one subject candidate area in which it is probable that a tracking target subject appears on an image that is received from an imaging unit; calculating a degree of blur of the subject candidate area for each of the subject candidate areas; determining that the subject appears in a subject candidate area having a degree of blur in accordance with a moving speed of the subject, out of the subject candidate areas; and deciding movement of the subject depending on a movement direction from an area in which the subject appears on a previous image that is captured by the imaging unit before capturing the image, to the subject candidate area in which the subject appears on the image.

Abstract: According to an aspect of an embodiment, a method of detecting boundary line information contained in image information comprising a plurality of pixels in either one of first and second states, comprising: detecting a first group of pixels in the first state disposed continuously in said image information to determine first line information and detecting a second group of pixels in the first state disposed adjacently with each other and surrounded by pixels in the second state to determine edge information based on the contour of the second group of pixels; and determining the boundary line information on the basis of the information of the relation of relative position of the line information and the edge information and the size of the first and second group of pixels.

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 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: 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: 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 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 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 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: 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.