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Image Retrieval Using Spacial Color Correlation and Local Texture Characteristics  

Sung, Joong-Ki (LG.PHILIPS LCD)
Chun, Young-Deok (Department of Electronic Engineering, KyungPook National University)
Kim, Nam-Chul (Department of Electronic Engineering, KyungPook National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.42, no.5, 2005 , pp. 103-114 More about this Journal
Abstract
This paper presents a content-based image retrieval (CBIR) method using the combination of color and texture features. As a color feature, a color autocorrelogram is chosen which is extracted from the hue and saturation components of a color image. As a texture feature, BDIP(block difference of inverse probabilities) and BVLC(block variation of local correlation coefficients) are chosen which are extracted from the value component. When the features are extracted, the color autocorrelogram and the BVLC are simplified in consideration of their calculation complexity. After the feature extraction, vector components of these features are efficiently quantized in consideration of their storage space. Experiments for Corel and VisTex DBs show that the proposed retrieval method yields 9.5% maximum precision gain over the method using only the color autucorrelogram and 4.0% over the BDIP-BVLC. Also, the proposed method yields 12.6%, 14.6%, and 27.9% maximum precision gains over the methods using wavelet moments, CSD, and color histogram, respectively.
Keywords
CBIR; Color autocorrelogram; BDIP; BVLC; Feature combination;
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