Color image retrieval using compressed chromaticity and color edge information

Color histogram is widely used in image retrieval due to its simplicity and fast operation speed. Since color histogram describes only global color distribution in an image, it is not robust to large changes in appearance and shape caused by viewing position, camera zoom, etc. To overcome this problem, we propose the method using the color edge information. Although changes in appearance and shape happen, the pair of colors on the color edge does not change. So we use the global distribution of pairs of colors on the color edge pixel to cope with large appearance change. In the proposed method, color edge detection based on vector angle is performed to classify the pixels of image into smooth and edge pixels. For edge pixel, the global distribution of pairs of colors around the edge is represented by 36 non-uniform colors. In the smooth pixel, color distribution is represented by 2D histogram of the opponent chromaticity (rg, by) and 2D histogram is compressed by DCT(Discrete Cosine Transform). Joint histogram of compressed the 2D chromaticity histogram and the global distribution of pairs of colors is very robust to large appearance change.