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Image Retrieval Using Combination of Color and Multiresolution Texture Features  

Chun Young-deok (경북대학교 전자공학과 영상통신 연구실)
Sung Joong-ki (LG.PHILIPS LCD)
Kim Nam-chul (경북대학교 전자공학과 영상통신 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.30, no.9C, 2005 , pp. 930-938 More about this Journal
Abstract
We propose a content-based image retrieval(CBIR) method based on an efncient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelograrn is chosen which is blown to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is hewn to measure local intensity variations well and measure local texture smoothness well, respectively. The texture features are obtained in a wavelet pyramid of the luminance component of a color image. The extracted features are combined for efficient similarity computation by the normalization depending on their dimensions and standard deviation vectors. Experimental results show that the proposed method yielded average $8\%\;and\;11\%$ better performance in precision vs. recall than the method using BDIPBVLC moments and the method using color autocorrelograrn, respectively and yielded at least $10\%$ better performance than the methods using wavelet moments, CSD, color histogram. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.
Keywords
CBIR; color autocorrelogram; BDIP; BVLC; multiresolution;
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Times Cited By KSCI : 1  (Citation Analysis)
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