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Image retrieval using both color and texture features

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1 Author(s)
Fan-Hui Kong ; Department of Information Science & Technology, Heilongjiang University, Harbin 150080, China

This paper has a further exploration and study of visual feature extraction. According to the HSV (Hue, Saturation, Value) color space, the work of color feature extraction is finished, the process is as follows: quantifying the color space in non-equal intervals, constructing one dimension feature vector and representing the color feature by cumulative histogram. Similarly, the work of texture feature extraction is obtained by using gray-level co-occurrence matrix (GLCM) or color co-occurrence matrix (CCM). Through the quantification of HSV color space, we combine color features and GLCM as well as CCM separately. Depending on the former, image retrieval based on multi-feature fusion is achieved by using normalized Euclidean distance classifier. Through the image retrieval experiment, indicate that the use of color features and texture based on CCM has obvious advantage.

Published in:

2009 International Conference on Machine Learning and Cybernetics  (Volume:4 )

Date of Conference:

12-15 July 2009