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An important problem in color-based image retrieval and video segmentation is to lack information about how color is spatially distributed. To solve this problem and enhance the performance of image and video analyses, a spatial color descriptor is proposed involving a color adjacency histogram and color vector angle histogram. The color adjacency histogram represents the spatial distribution of color pairs at color edges in an image, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, the color vector angle histogram represents the global color distribution of smooth pixels in an image. Since the proposed color descriptor includes spatial adjacency information between colors, it can robustly reduce the effect of a significant change in appearance and shape in image and video analyses. Moreover, since the color adjacency histogram is simply represented by binary streams, the storage space required for the image histogram values can be effectively reduced. Experimental results show that even with significant appearance changes, the proposed color descriptor could produce a high image retrieval rate and accurately detect abrupt scene-cuts in a video analysis.