Comparing images using color coherence vectors

Color histograms are used to compare images in many applications. Their advantages are e#ciency, and insensitivity to small changes in camera viewpoint. However, color histograms lack spatial information, and this can cause images with very different appearances to have similar histograms. For example, a picture of fall foliage might contain a large number of scattered red pixels; this could have a similar color histogram to a picture of a single large red object. We describe a histogram-based method for comparing images that incorporates spatial information. While a color histogram counts the number of pixels with a given color, a color coherence vector #CCV# measures the spatial coherence of the pixels with a given color. If the red pixels in an image are members of large red regions, this color will have high coherence, while if the red pixels are widely scattered it will havelow coherence. CCVs can be computed at over 5 images per second on a standard workstation. A da...