Computational similarity based on chromatic barycenter algorithm

We propose in this paper a novel histogram-based chromatic barycenter algorithm for computing the similarity between images. The algorithm is simple, intuitive, and thus easy to implement. With its high precision and recall rates, the algorithm can be used as retrieval and scene change detection methods in very large video and image databases. When being used to process DCT based compressed data, the algorithm is even more efficient, as some of the time consuming decompression procedures can be skipped. This makes the algorithm an ideal tool for realtime and interactive multimedia applications with JPEG and MPEG data.