Similar Shape Retrieval in MARS

This paper presents a novel approach to representing 2-dimensional shapes that adaptively models different portions of the shape at different resolutions, having higher resolution where it improves the quality of the representation and lower resolution elsewhere. The proposed representation is invariant to scale, translation, and rotation. The representation is amenable to indexing using existing multidimensional index structures and can thus support efficient similarity retrieval. The experiments reported here show that the adaptive resolution technique performs significantly better compared to the fixed resolution approach previously proposed in the literature.
Prepared in cooperation with the Department of Information and Computer Science, University of California at Irvine, Irvine, CA. Sponsored in part by the National Science Foundation under Grant No. IIS-9734300 and the NSF/DARPA/NASA Digital Library Initiative Program under Cooperative Agreement No. 94-11318.