Shape similarity based on contour decomposition and correspondence

A shape similarity measure based on contour decomposition and part correspondence is introduced. Shapes are approximated by polygons with split-and-merge technique, and a set of perceptual and easily reconfigurable attributes are designed to model the polygonal curves. To compute our similarity measure, the correspondence of polygonal curves is established by DP technique. Then, the similarity between them is computed and aggregated. To verify the effectiveness of our algorithm, we apply it to shape retrieval in two different datasets, one of marine species shapes and another of mechanical shapes, and compare it with some traditional approaches