Abstract: The present invention relates to an apparatus and method for recognizing biological named entity from biological literature based on united medical language system (UMLS). The apparatus and the method receives metathesaurus from the UMLS, constructs a concept name database, a single name database and a category keyterm database, which are language resources to be used recognize a named entity, receives each concept name stored in the concept name database, extracts features of each of the concept names by using data stored in the single name database and the category keyterm database, constructs a rule database by creating rules used to recognize the named entity and filtering the rules by using the extracted features, receives a biological literature, extracts nouns and noun phrases that are candidate named entities, applies the rules stored in the rule database to the nouns and the noun phrases, and recognizes the named entities.

Abstract: A method for generating a block-based image histogram from data compressed by JPEG, MPEG-1, and MPEG-2, or uncompressed image data employing block-based linear quantization to generate histograms that include color, brightness, and edge components. The edge histogram, in particular, includes the global edge features, semi-global edge features, and local edge features. The global edge histogram is based on image blocks of the entire image space. The local edge histogram is based on a group of edge blocks. The semi-global edge histogram is based on the horizontally and the vertically grouped image blocks. A method for generating block-based image histogram with color information and brightness information of image data in accordance with an embodiment of the present invention extracts feature information of an image in terms of the block and updates global histogram bins on the basis of the feature information.

Abstract: A method for generating a block-based image histogram from data compressed by JPEG, MPEG-1, and MPEG-2, or uncompressed image data employing block-based linear quantization to generate histograms that include color, brightness, and edge components. The edge histogram, in particular, includes the global edge features, semi-global edge features, and local edge features. The global edge histogram is based on image blocks of the entire image space. The local edge histogram is based on a group of edge blocks. The semi-global edge histogram is based on the horizontally and the vertically grouped image blocks. A method for generating block-based image histogram with color information and brightness information of image data in accordance with an embodiment of the present invention extracts feature information of an image in terms of the block and updates global histogram bins on the basis of the feature information.

Abstract: A method for constructing a database having image information representing a plurality of images including the steps of: a) calculating L×5 number of normalized edge histogram bins to generate L number of edge histograms of a target image, wherein each edge histogram has five normalized edge histogram bins and represents a spatial distribution of five reference edges in a sub-image and L is a positive integer, wherein the reference edges include four directional edges and a non-directional edge; b) non-linearly quantizing the L×5 number of normalized edge histogram bins to generate L×5 number of quantization index values for the target image; c) storing the L×5 number of quantization index values to the database; and d) repeating the steps a) to c) until all of the stored images are processed to thereby construct the database having the image information.

Abstract: An apparatus and method for searching color and shape of image data based on a natural language with Fuzzy concept is disclosed.