Currently there are quite a few image retrieval systems that use color and texture as features to search images. However, by using global features these methods retrieve results that often do not make much perceptual sense. It is necessary to constrain the feature extraction within homogeneous regions, so that the relevant information within these regions can be well represented. This paper describes our recent work on developing an image segmentation algorithm which is useful for processing large and diverse collections of image data. A compact color feature representation which is more appropriate for these segmented regions is also proposed. By using the color and texture features and a region-based search, we achieve a very good retrieval performance compared to the entire image based search.