Abstract: A color image processing method is provided. The color image processing method includes the step of: (a) indexing a color image by assigning representative colors of an image to a color space divided into a plurality of regions. The color image processing method may be applied to object-based image processing such as MPEG-7, and fast search and retrieval of multimedia content can be made.

Abstract: A color image processing method for retrieving a color feature descriptor for describing color features of an image is provided. The color image processing method includes the steps of (a) obtaining color vectors of an input image, (b) classifying the color vectors to obtain dominant colors of the input image and the ratios thereof, and (c) representing the dominant colors and the ratios thereof as a color feature descriptor of the input image. The color image processing method is applied to an object-based image processing method, thereby allowing fast search and retrieval of multi-media contents.

Abstract: A database building method for multimedia contents is provided. The database building method for multimedia contents has the steps of (a) accessing an arbitrary site providing multimedia contents through a telecommunications network; (b) calling multimedia contents in by spidering the site; and (c) classifying the multimedia contents data according to the stored addresses and storing them in a predetermined database. Using category information on the corresponding sites, the database building method for multimedia contents according to the present invention semantically classifies multimedia contents and stores them in the corresponding databases. In the database built by the database building method for multimedia contents according to the present invention, multimedia contents which are dispersed on the WWW are well collected and, using category information or URL information, are semantically well classified.

Abstract: A method for retrieving an image texture descriptor for describing texture features of an image, including the steps of (a) filtering input images using predetermined filters having different orientation coefficients, (b) projecting the filtered images onto axes of each predetermined direction to obtain data groups consisting of averages of each directional pixel values, (c) selecting candidate data groups among the data groups by a predetermined classification method, (d) determining a plurality of indicators based on orientation coefficients of the filters used in filtering the candidate data groups, and (e) determining the plurality of indicators as the texture descriptor of the image. The texture descriptors which allow kinds of texture structure present in an image to be perceptually captured can be retrieved.

Abstract: A method for retrieving an image texture descriptor for describing texture features of an image, including the steps of (a) filtering input images using predetermined filters having different orientation coefficients, (b) projecting the filtered images onto axes of each predetermined direction to obtain data groups consisting of averages of each directional pixel values, (c) selecting candidate data groups among the data groups by a predetermined classification method, (d) determining a plurality of indicators based on orientation coefficients of the filters used in filtering the candidate data groups, and (e) determining the plurality of indicators as the texture descriptor of the image. The texture descriptors which allow kinds of texture structure present in an image to be perceptually captured can be retrieved.

Abstract: A video image searching method and apparatus that partially restores a picture according to a determined image restoring ratio, in order to reduce the searching time required compared to complete restoration of the picture as in conventional video image search. In the image searching method and apparatus, a dominant image element is extracted using a fractal image compression method, so that the image is partially restored, to thereby effectively search for the video image.

Abstract: A digital image segmentation method and device is provided. The method includes the steps of grouping an image stream into a plurality of continuous frame groups, setting one arbitrary frame as an I frame and the others as P frames in each group, segmenting the I frame into a plurality of regions, and segmenting the P frames by obtaining motion vectors, using motion prediction, of the segmented I frame regions, respectively, with respect to each of the P frames, by moving the segmented I frame regions by the respective motion vectors, and by setting the moved I frame regions as segmented P frame regions. Accordingly, the segmentation of the I frame is applied to the P frame segmentation, and a conventional segmentation process consuming excessive time with respect to all frames does not need to be performed. Thus, rapid segmentation can be performed.

Abstract: A video image searching method and apparatus that partially restores a picture according to a determined image restoring ratio, in order to reduce the searching time required compared to complete restoration of the picture as in conventional video image search. In the image searching method and apparatus, a dominant image element is extracted using a fractal image compression method, so that the image is partially restored, to thereby effectively search for the video image.

Abstract: An apparatus for analyzing image texture information and a method therefor are provided. The apparatus for analyzing the image texture information includes a filtering unit for filtering a still image including a plurality of pixels of M rows×N columns with filters having different filtering coefficients, an X axis projector for calculating a gray level mean value of a row of N pixels, for each row, with respect to the filtered plurality of images, and a Y axis projector for calculating a gray level mean value of a column of M pixels, for each column, with respect to the filtered plurality of images. It is possible to describe the orientation and the periodicity of the texture in extracting the texture information.

Abstract: A database building method for multimedia contents is provided. The database building method for multimedia contents has the steps of (a) accessing an arbitrary site providing multimedia contents through a telecommunications network; (b) calling multimedia contents in by spidering the site; and (c) classifying the multimedia contents data according to the stored addresses and storing them in a predetermined database. Using category information on the corresponding sites, the database building method for multimedia contents according to the present invention semantically classifies multimedia contents and stores them in the corresponding databases. In the database built by the database building method for multimedia contents according to the present invention, multimedia contents which are dispersed on the WWW are well collected and, using category information or URL information, are semantically well classified.

Abstract: Digital image coding/decoding apparatus using watermarking, and methods thereof are provided.

Abstract: An apparatus for searching a digital image and a method therefor are provided. The digital image search apparatus includes a database processing unit for segmenting an image from the database or an image which is not stored in the database into homogeneous regions and analyzing and storing the segmented regions and an image search engine unit for searching for an image having a segmented region showing a characteristic similar to the characteristic of the query region. It is possible to perform detailed and efficient searching work since it is possible to perform a region-based search by means of segmented regions and a user can perform searching by selecting the characteristic and the position of the segmented regions.

Abstract: A method for describing pattern repetitiveness which may exist within an image, is provided. The method of describing pattern repetitiveness of an image comprises: (a) projecting an image on a predetermined axis having a predetermined direction, (b) decomposing the projected image down one level, (c) increasing a threshold value until a pattern quantizing value is retained, and denoising the decomposed data, and (d) describing pattern repetitiveness of the image using the pattern quantizing value of the denoised data and the threshold value used for denoising. Because the method of describing pattern repetitiveness of an image effectively denoises the original image without damaging the pattern repetitiveness of the original image, and the pattern repetitiveness is described using the denoised data, it is possible to describe more definite pattern repetitiveness.

Abstract: A method of measuring a similarity between images is provided. The method includes the steps of (a) computing a statistical dissimilarity between the images; (b) computing a perceptual dissimilarity between the images; and (c) computing a dissimilarity between the texture features of the images based on the statistical dissimilarity and the perceptual dissimilarity. When images perceptually similar to a query image are searched and retrieved according to the above measuring method, the possibility that the retrieved images are not perceptually similar to the query image is small. Accordingly, the image searching performance can be improved when searching images having texture features similar to that of a query image.

Abstract: An indexing method of a feature vector data space, which can be used for a similarity search in a multidimensional vector space, is provided. The indexing method includes the steps of (a) determining whether at least one cell, on which feature vectors are concentrated, exists, and (b) hierarchically indexing the feature vector data space when it is determined that at least one cell, on which feature vectors are concentrated, exists in the step (a). Accordingly, the feature vector data space can be finely indexed when feature vectors are not uniformly distributed in a high-dimensional vector space.

Abstract: A clothes washing machine has a controller which can be set for a winter operation mode, i.e., when the wash water is relatively cold. In the winter operation mode, the weight of laundry articles in the wash tub is determined. If the weight is less a reference weight, the laundry articles are washed for a first time period. If the weight is more than the reference weight, the laundry articles are washed for a longer time period.