The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Sep. 12, 2006
Filed:
Jun. 30, 2004
Soo Jun Park, Taejon, KR;
Chee Sun Won, Seoul, KR;
Dong Kwon Park, Seoul, KR;
Dong See Choi, Chungcheongnam-do, KR;
Seong Joon Yoo, Taejon, KR;
Hyun Jin Kim, Taejon, KR;
Soo Jun Park, Taejon, KR;
Chee Sun Won, Seoul, KR;
Dong Kwon Park, Seoul, KR;
Dong See Choi, Chungcheongnam-do, KR;
Seong Joon Yoo, Taejon, KR;
Hyun Jin Kim, Taejon, KR;
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. The method for generating block-based image histogram with color information and brightness information of image data minimizes quantization error by employing linear weight and updates values of histogram bins. The error that occurs at a boundary between bins of the histograms and the linear weight depends on the distance between the histogram bins.