Abstract: A first combination of feature and processing content of image data is stored in a storing unit in a first period, and a second combination of feature and processing content of image data is stored in the storing unit in a second period that is later in terms of time. When a change in processing content is detected between the first period and the second period, an updating unit updates the first combination to the second combination. An acquiring unit acquires a processing content for target image data based on a combination of feature and processing content stored in the storing unit. An output unit outputs the processing content acquired by the acquiring unit.

Abstract: A character area is extracted from an original image, which is a digital image, according to a feature value calculated with respect to the original image. Pixels belonging to the extracted character area are classified into a first class and a second class according to colors, in each of blocks divided from the original image. A black character color and a ground color on the original image are estimated according to the classification of the pixels belonging to the extracted character area into the first and second classes. A tone correction is performed to the original image according to the estimated black character color and the estimated ground color so as to adjust a contrast of the black character and the ground in an output image.

Abstract: An image processing apparatus includes a reduced image generating part generating a reduced image having a lower resolution than that of an original digital image. A first extracting part distinctly extracts a first foreground image and a first background image from the reduced image. A first continuous tone converting part converts, into a continuous tone, a halftone dot pattern of the first background image extracted from the reduced image. A combining part combines the first background image of which halftone dot pattern is converted into the continuous tone and an image based on the first foreground image extracted by the first extracting part.

Abstract: A show-through is removed as follows. Resolution of the color image is reduced and the color coordinate system is transferred to a one having a high independence. Then, edge intensity is calculated, edge-detection is performed. Then, color threshold processing is performed on a region except the edge to estimate a background color image, and the show-through removed image is synthesized. Edge difference image is calculated from respective edge intensity of the original image and the show-through removed image, any portion where the image is degraded due to inadequate processing is detected, a scale for processing (the size of a window) around such portion is reduced and the same processing is performed again. A show-through portion is then identified by calculating a difference between the show-through removed image and the reduced original image, the show-through portion is removed, and the image is printed.

Abstract: Image data is classified to identify the type of the image data using a feature amount of the image data calculated based on the layout (rough spatial arrangement and distribution of texts and photographs or pictures). Based on the result, a region extraction method that is associated with the type of the image data is selected for layout analysis. According to the region extraction method, the image data is divided into regions.

Abstract: A first area extracting unit extracts a first document area from document image data by dividing the document image data in units of a document area. A language determining unit determines a type of a language used in the document image data. A second area extracting unit extracts a second document area by dividing or combining the first document area based on a rule corresponding to the type of the language determined by the language determining unit.

Abstract: An image processing apparatus includes a character-area extracting unit that extracts a character area in which characters are displayed from image data including characters, a character-color converting unit that converts the color of characters in the character area extracted by the character-area extracting unit to a predetermined prescribed character color, and a background-color converting unit that converts a background color of the background, which is an area other than the characters in the character area extracted by the character-area extracting unit to a predetermined prescribed background color.

Abstract: An apparatus, method, system, computer program and product, each capable of applying document layout analysis to a document image with control of a non-character area. A non-character area is extracted from a document image to be processed. A character image is generated from the document image by removing the non-character area from the document image. The character image is segmented into a plurality of sections to generate a segmented image. The segmented image is adjusted using a selected component of the non-character image to generate an adjusted segmented image. A segmentation result is output, which is generated based on the adjusted segmented image.

Abstract: An apparatus, method, system, computer program and product, each capable of inputting an input image; obtaining an image object indicating image processing to be applied to the input image; and managing a state of the image object and transition of the state.

Abstract: An apparatus, method, system, computer program and product, each capable of extracting a background area of a document image. The background area of the document image may be extracted by repeating recursively the acts of: extracting a set of white rectangles from a processed area of the document image; dividing the processed area into a plurality of segments using the set of white rectangles as a separator; storing the plurality of segments; and reading the plurality of segments in a predetermined order as a processed area.

Abstract: An image processing system is provided that performs object-oriented image processing and collectively manages image data, image elements, and the history and state of the image processing. In this image processing system, an original image object to be normalized is generated for image data to be processed. Next, the normalized image data is converted into the optimum image data format in compliance with the purpose of use, using an optimizing object. The generation of the object and the condition setting and changes are performed by the same methods (functions) in the object.

Abstract: A method, apparatus and system, each capable of recognizing or reproducing a character color, are disclosed. An original image is divided into a character image and a background image. The color information of the character image is obtained to generate a color palette of the character image. A color, defined by the color palette, is assigned to each of the characters in the character image. The color palette may include a main color palette and a minor color palette.

Abstract: An apparatus, method, system, and computer program and product, each capable of generating normalized image data from original image data are disclosed. To generate the normalized image data, feature information is extracted from the original image data, and predetermined image processing is applied to the original image data using the feature information.

Abstract: A method, apparatus, system, and program for image processing are provided to perform operations of recognizing, reproducing, and enhancing an image, particularly one having character, symbol, or line-segment portions. An image obtainer obtains a multivalue image of color or grayscale. A brightness image generator generates a brightness image of the multivalue image, representing brightness values of respective pixels of the multivalue image. A topographic feature image generator generates a topographic feature image of the multivalue image, having a topographic feature corresponding to the brightness values. A topographic feature adder generates a binary image of the multivalue image, by using information contained in the topographic feature.

Abstract: In a digital halftoning method and apparatus of the invention, a visual-quality control filter is provided based on computation of a quantity of local features of neighboring pixels for each of respective pixels of a gray-scale image, the visual-quality control filter adaptively controlling visual characteristics for each of respective pixels of an image input to the filter. An initial halftone image is generated from the gray-scale image. The gray-scale image is processed through the visual-quality control filter to output a processed gray-scale image with the controlled visual characteristics. The initial halftone image is processed through the visual-quality control filter to output a processed initial halftone image with the controlled visual characteristics. A sum of squares of local visual-quality errors between the processed gray-scale image and a processed halftone image is computed, wherein the computation is started by taking the processed initial halftone image as a first processed halftone image.

Abstract: A character area is extracted from an original image, which is a digital image, according to a feature value calculated with respect to the original image. Pixels belonging to the extracted character area are classified into a first class and a second class according to colors, in each of blocks divided from the original image. A black character color and a ground color on the original image are estimated according to the classification of the pixels belonging to the extracted character area into the first and second classes. A tone correction is performed to the original image according to the estimated black character color and the estimated ground color so as to adjust a contrast of the black character and the ground in an output image.

Abstract: A method of obtaining a 3-dimensional shape of an object from a sequence of image frames includes the steps of a) generating a tracking matrix which has matrix elements representing coordinates of feature points of the object tracked through the sequence, and has each row representing a corresponding image frame and each column representing a corresponding feature point, wherein some of the matrix elements are missing, b) generating an estimation matrix as a sub-matrix of the tracking matrix by selecting rows and by selecting a column of a given feature point and columns of a predetermined number of feature points closest to the given feature point, such that the estimation matrix has matrix elements thereof missing only for the given feature point in a single image frame, c) calculating estimates of the missing matrix elements of the estimation matrix, d) repeating the steps b) and c) to obtain estimates of remaining missing matrix elements of the tracking matrix, and e) obtaining a 3-dimensional shape of th

Abstract: An image processing apparatus includes a reduced image generating part generating a reduced image having a lower resolution than that of an original digital image. A first extracting part distinctly extracts a first foreground image and a first background image from the reduced image. A first continuous tone converting part converts, into a continuous tone, a halftone dot pattern of the first background image extracted from the reduced image. A combining part combines the first background image of which halftone dot pattern is converted into the continuous tone and an image based on the first foreground image extracted by the first extracting part.

Abstract: A figure is input, and structural features of the input figure are extracted. Structural features of deformed figures are produced, in accordance with a specific transformation rule, from the extracted structural features. The input figure is classified based on the structural features thus extracted and thus produced.

Abstract: A show-through is removed as follows. Resolution of the color image is reduced and the color coordinate system is transferred to a one having a high independence. Then, edge intensity is calculated, edge-detection is performed. Then , color threshold processing is performed on a region except the edge to estimate a background color image, and the show-through removed image is synthesized. Edge difference image is calculated from respective edge intensity of the original image and the show-through removed image, any portion where the image is degraded due to inadequate processing is detected, a scale for processing (the size of a window) around such portion is reduced and the same processing is performed again. A show-through portion is then identified by calculating a difference between the show-through removed image and the reduced original image, the show-through portion is removed, and the image is printed.