AMethod for similarity based retrieval for a large multimedia database

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We propose an algorithm and data structure for fast computation of similarity based on Jaccard coefficient to retrieve images by composition. The similarity measures the degree of overlap between the regions of an image and those of another image. The key idea for fast computation of the similarity is to use the runlength description of an image for computing the number of overlapped pixels between the regions of an image and those of another image. We present an algorithm and data structure, and experiment on 30,000 images to evaluate the performance of our algorithm. Experiments show that the proposed algorithm is 5.49 (2.36) times faster than a naive algorithm on the average (the worst). Finally, we theoretically give fairly good estimations of the number of runs, computation time and the size of a runlength file.