2D shape matching based on B-spline curves and Dynamic Programming

In this paper, we propose an approach for two-dimensional shape representation and matching using the B-spline modelling and Dynamic Programming (DP), which is robust with respect to affine transformations such as translation, rotation, scale change and some distortions. Boundary shape is first splited into distinct parts based on the curvature. Curvature points are critical attributes for shape description, allowing the concave and convex parts of an object representation, which are obtained by the polygonal approximation algorithm in our approach. After that each part is approximated by a normalized B-spline curve using some global features including the arc length, the centroid of the shape and moments. Finally, matching and retrieval of similar shapes are obtained using a similarity measure defined on their normalized curves with Dynamic Programming. Dynamic programming not only recovers the best matching, but also identifies the most similar boundary parts. The experimental results on some benchmark databases validate the proposed approach.