A METHOD OF COLOR-SPATIAL HISTOGRAM FOR IMAGE SIMILARITY PATTERNS MINING

Color histograms are widely used for content-based image retrieval because they are trivial and effective to compute, not sensitive to size and orientation, and robustly tolerate movement of objects in the image and changes in camera viewpoint. However, a color histogram only records an image’s overall color compositions and no any spatial information is included, so the retrieval precision is limited. In this paper, a color-spatial histogram is proposed, which incorporates spatial information with color compositions without sacrificing the robustness of color histograms. The purpose is to consider the representation role of color compositions and spatial information in the meantime. Each entry in a color-spatial histogram is the color frequency and corresponding position information of the virtual boundary. Experimental evidence suggests that this new color-spatial histogram outperforms not only the traditional color histogram method but also the cumulative color histogram method for image retrieval.