Shape Matching with Occlusion in Image Databases
نویسندگان
چکیده
Abstract. We propose an approach for matching deformed, occluded and unoccluded shapes using Dynamic Programming (DP). We distinguish among various cases of matching including cases where the shapes are scaled with respect to each other or cases where one shape matches the whole or only a part of the other shape. Our approach handles noise and shape distortions by allowing matching of merged sequences of consecutive small segments in a shape, with larger segments of another shape, while being invariant to translation, scale orientation and starting point selection. We demonstrate the superiority of our approach over traditional approaches to shape matching and retrieval based on Fourier descriptors and moments.
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