Image Retrieval Using Combination of Color andMultiresolution Texture Features 


Vol. 30,  No. 9, pp. 930-938, Sep.  2005


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  Abstract

We propose a content-based image retrieval(CBIR) method based on an efficient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelogram is chosen which is known to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is known 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 autocorrelogram, 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.

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  Cite this article

[IEEE Style]

Y. Chun, J. Sung, N. Kim, "Image Retrieval Using Combination of Color andMultiresolution Texture Features," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 9, pp. 930-938, 2005. DOI: .

[ACM Style]

Young-deok Chun, Joong-ki Sung, and Nam-chul Kim. 2005. Image Retrieval Using Combination of Color andMultiresolution Texture Features. The Journal of Korean Institute of Communications and Information Sciences, 30, 9, (2005), 930-938. DOI: .

[KICS Style]

Young-deok Chun, Joong-ki Sung, Nam-chul Kim, "Image Retrieval Using Combination of Color andMultiresolution Texture Features," The Journal of Korean Institute of Communications and Information Sciences, vol. 30, no. 9, pp. 930-938, 9. 2005.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880