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A Study of Order-Based Block Color Feature Image Retrieval Compared with Cumulative Color Histogram Method

Color is one of the most important features in image retrieval. Color histograms have proved to be stable representations of an image, but they might be similar in different kinds of images because they describe the global intensity distribution of images. A new color image representation method is proposed in this paper. At first, each color channel (R, G, B) of an image is divided into 48 blocks (6 rows X 8 columns). Secondly, statistical features are computed to characterize the block’s color feature. Finally, all block features are combined to form an image’s color feature. The experimental results show that the retrieval effectiveness of the proposed technique is better than color histogram-based method.