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Color image retrieval with adaptive feature weight in Brushlet domain

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4 Author(s)
Xiaohui Yang ; Inst. of Appl. Math., Henan Univ., Kaifeng, China ; Zhongye Wang ; Dengfeng Li ; Jing Zhang

This paper presents a method for extracting texture and color hybrid features and constructing an adaptive weight operator, which can be used for content-based image retrieval (CBIR). This method extracts texture feature effectively based on Brushlet transform, quantifies in the HSV space, and extracts color feature by color histogram. K-mean clustering is introduced to count overall characteristics of images and to classify images. Moreover, in considering the distinction between images, an adaptive feature weight operator is constructed. Experiments show that average precision of our method has increased by 12% compared with hybrid features of traditional weight-based.

Published in:

Web Society (SWS), 2010 IEEE 2nd Symposium on

Date of Conference:

16-17 Aug. 2010