A new color model HMMD is disclosed based upon hue, the shade, the tone, the tint and the brightness of a color, and a color quantizing method using the HMMD color space. The present invention regards the colors adjacent to a given color in the color space as the neighboring colors to consider indices of the neighboring colors as the partial values according to the distance. Accordingly, the present invention can accomplish a color quantization close to the change of the color sensed by the human eye, thereby capable of enhancing a performance of the image searching system based on content.

HMMD color space and method for quantizing color using HMMD space and color spreading

An information processing method, comprising acquiring a photographed image of a color sample including specific color markers, binarizing a signal indicating luminosity of the photographed image, detecting a marker area, plotting a color signal of the marker area on a color plane, labeling for a plotting result, and setting a color recognition parameter for identifying the color area of the specific color markers from the labeling result.

Information processing method

An image processing apparatus is disclosed, including a modification part, a model creation part, and a division part. The modification part instructs modification of a portion of a foreground area or a background area which is erroneously divided as a result of dividing predetermined image data into the foreground area being an extraction target and the background area being an out-of-extraction target. The model creation part creates a foreground model of the foreground area and a background model of the background area which are modified, based on first pixel values of a predetermined line segment where the modification is instructed and second pixel values of the foreground area and the background area which are divided. The division part divides the image data into the foreground area and the background area by using the foreground model and the background model which are created by the model creation part.

Image processing apparatus, image processing method, and computer-readable recording medium

PROBLEM TO BE SOLVED: To provide an image correction system for varying the color of an image which is especially robust for an object reflected on the image. SOLUTION: The image correction system comprises a section 1 for inputting a processing object image and a reference image of correction processing, a color space dividing section 2 for extracting a processing object region and a corresponding reference region becoming a pair of color space conversion from the reference image, a color space converting section 3 for converting the color of the processing object image based on the reference image by utilizing the processing object region and the reference region extracted at the color space dividing section 2, and a section 4 for processing the processing object image inputted at the image input section 1 in a predetermined format based on the processing results from the color space converting section 3 and outputting the resultant image. COPYRIGHT: (C)2008,JPO&INPIT

Image correction system, method and program

Embodiments of the claimed subject matter provide a system and process for enhancing the display of color in a graphical display. In one embodiment, a process is provided for color enhancement using a detection volume and a shift volume. In one embodiment, input from pixels, as color data, is compared to a detection volume. If the color data of an input is detected in the detection volume, the color data is modified to a corresponding position in the shift volume, the modification consisting of an enhancement to the original color.

Method and system for color enhancement with color volume adjustment and variable shift along luminance axis

PURPOSE:To correct the color of a specific area by the clustering method efficiently by applying clustering in a space to execute area division, designating the area on a display device so as to correct the color of the designated area thereby using the new clustering method. CONSTITUTION:The method is made up of a color space transformation section 10, a transformation section 20 to a characteristic space, an area division section 30, an area designation section 40, a color correction section 50 and an inverse transformation section 60. In the case of color correction of a specific area of a color picture, a characteristic of distribution on a color space estimated from a reflection model of an object is modelled as a curve passing from a 'black' and 'object color' and reaching 'white' and each picture element is mapped onto a parameter space where curves are distinguished to obtain a distribution in which picture elements of the same area are in existence locally at a specific location and the area is divided by applying clustering in the space and an area is designated on a display device to correct the color of the designated area.

Color correction method for specific area of color picture

PROBLEM TO BE SOLVED: To easily execute color tone correction by distributing each picture element value in a color space at an equal interval in the direction of lightness and moving each division area in the color space so as to correct the color tone. SOLUTION: A position in an image desired to be corrected is pointed out and, a correction area extract section 24 generates mask data. The generated mask data are outputted to an image data conversion section 30. On the other hand, a correction instruction section 18 enters a color tone correction instruction word and when a data storage section 22 selects a corresponding distribution displacement vector, it is given to a characteristic curve arithmetic section 28, in which a change amount characteristic curve corresponding to L, C, H is obtained through an interpolation arithmetic operation based on the distribution change vector. When the change amount characteristic curve is obtained, it is inputted to an image data conversion section 30. Then mask data are applied to image data received separately from an image storage memory 12 and picture element value conversion is executed only for picture elements in the image whose mask is released and the result is outputted to the memory 12.

Image color tone correcting device

PURPOSE:To effectively compress a data while keeping satisfactory picture quality by obtaining an optimum representative value vector at an optimum level for each block, encoding all the picture elements in the block based on this representative value vector and further encoding them according to a complete restoration encoding method. CONSTITUTION:A system for compressing (encoding) and reproducing (decoding) a picture data is equipped with an encoder 10 for encoding the picture data and communicating and storing the encoded data and a decoder part 12 for reproducing the encoded data to the picture data. In this case, the data in each block is divided into groups corresponding to the optimum quantizing level by using splitting algorithm, the optimum representative value is prepared, and the data in the block is encoded based on the prepared representative value vector and further encoded by the complete restoration encoding method. Thus, the picture suitable for printing can be secured and further, the amount of data can be reduced.

Method for compressing picture data for printing

PURPOSE:To execute a better area division by modeling the feature of a distribution on a color space estimated from the reflection model of an object as a curve for passing through 'object color' from 'black' and reaching 'white', and executing clustering on a parameter space for distinguishing this curve. CONSTITUTION:The feature of a distribution on a color space estimated from the reflection model of an object is modeled as a curve for passing through 'object color' from 'black' and reaching 'white'. By mapping each picture element onto a parameter space for distinguishing its curve, such a distribution as each picture element in the same area is localized in a specific place is obtained, and clustering is executed on its space. Also, since cluster representative points 1-3 correspond to one piece of half ellipse for representing the area, after a division is executed in such a manner, for which half ellipse each picture element belongs is decided, labeling is executed and the area division is finished. Thus, the picture element in the same area comes to be localized easily in a specific place on the parameter space.

Area dividing method for color image

PURPOSE:To attain efficient coding by mapping picture elements onto a parameter space, applying clustering to the picture elements on the space, dividing the space into areas and coding individually division information, lightness information and chromaticity error information. CONSTITUTION:A color space transformation section 10 transforms an input RGB signal into an Luu signal and a feature space transformation section 20 transforms the transformed signal into a point Luu in the feature space. An area division section 30 adopts the ISODATA method to implements 2-dimension clustering and to divide the area. Then an area information coding section 42 codes the information subjected to area division on a chromaticity space and a lightness information coding section 44 applies orthogonal transformation to a lightness signal L to implement coding. Furthermore, a chromaticity error information coding section 46 hardly detects deterioration in the chromaticity in comparison with the lightness, error information between an area division picture and an original picture is thinned to implement coding by orthogonal transformation. Each picture element is mapped on a feature space and clustered in this way, the efficient coding is executed.

Data compression coding method for color picture

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