In this paper

a robust content-based color image retrieval algorithm using multiple features is proposed. This algorithm takes into consideration the important image edges and utilizes the support vector regression(SVR) theory. Firstly

the image denoising and color edge detection are performed using the SVR classification. Secondly

the whole color edge is divided into local grids; and the color histograms and texture histograms for local grids are computed as image features. Finally

the similarity between color images is computed by using a combined feature index based on the color histogram and texture histogram for local grids. Experimental experiments

including comparisons with many state-of-the-arts

show the effectiveness of our algorithm in improving the retrieval performance(especially for noisy images).