A New Method for Boundary-Based Shape Matching and Retrieval

This paper presents a novel method for efficient boundary based shapes matching and retrieval in presence of occlusion. In this method, the geometric and topological information of boundary curves are encoded in the form of longest common subcurves (LCS) graphs and their similarity is estimated by graph matching. B-Spline is used for approximating the original boundary, then inflection points are detected to split such a B-spline to convex/concave segments. The characteristic string is constructed based on these segments' canonical frame. After LCS candidates are found, their graphs which are constructed by using its segments as vertices and the weighted walkthrough (WW) between two segments as edges are compared to obtain the optimal match. Thorough experimental results and comparisons demonstrate that our method outperforms traditional LCS or dynamic programming based methods in shape matching and enhances the quality of inexact shape retrieval, in particular in the presence of occlusions and affine transformation.