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We propose in this paper a new approach to combine color and spatial features for content-based image retrieval applications. The color feature is derived using a fuzzy c-means clustering algorithm in a perceptually uniform color space. To further improve the image discrimination power, the spatial information of each image is measured by a multi-scale color histogram set derived from a set of hierarchical image partitions. The proposed method is capable of representing each image compactly and retrieving similar images effectively. Experimental results suggest that the proposed method can achieve consistently better performance compared to those using the popular conventional color histogram and generalized color histogram.