Shape similarity matching for query-by-example
This paper describes a unified approach for two-dimensional (2-D) shape matching and similarity ranking of objects by means of a modal representation. In particular, we propose a new shape-similarity metric in the eigenshape space for object/image retrieval from a visual database via query-by-example. This differs from prior work which performed point correspondence determination and similarity ranking of shapes in separate steps. The proposed method employs selected boundary and/or contour points of an object as a coarse-to-fine shape representation, and does not require extraction of connected boundaries or silhouettes. It is rotation-, translation- and scale-invariant, and can handle mild deformations of objects (e.g. due to partial occlusions or pose variations). Results comparing the unified method with an earlier two-step approach using B-spline-based modal matching and Hausdorff distance ranking are presented on retail and museum catalog style still-image databases.
modal matching image databases shape similarity metrics object retrieval content-based access