A sound algorithm for region-based image retrieval using an index

Region-based image retrieval systems aim to improve the effectiveness of content-based search by decomposing each image into a set of "homogeneous" regions. Thus, similarity between images is assessed by computing similarity between pairs of regions and then combining the results at the image level. We propose the first provably sound algorithm for performing region-based similarity search when regions are accessed through an index. Experimental results demonstrate the effectiveness of our approach, as also compared to alternative retrieval strategies.