A matching algorithm of deformed planar curves using multiscale convex/concave structures

This paper proposes a new multiscale segment matching method which is applicable to heavily deformed planar shapes. First, multiscale representations are obtained using curvature scale space filtering. Then inflection point correspondence is developed between consecutive smoothed shapes. The representation in this paper, unlike the well-known curvature scale space image description, ensures that it always satisfies the consistency of hierarchical segment replacement. Moreover, it requires less processing time and memory allocation. Finally, optimum scale segments are matched by a new multiscale segment matching method proposed herein. In this method, the matching problem is formulated as a minimization problem of the total amount of segment dissimilarity. The minimization problem is solved effectively using dynamic programming. The proposed matching method makes it possible to obtain intuitively relevant correspondences even if the shapes have some local heavy deformation.