A Spectral Matching for Shape Retrieval Using Pairwise Critical Points

Abstract

The matching and retrieval of shapes is an important challenge in computer vision. A large number of shape similarity approaches have been developed. In this paper, we employ two approaches for improving shape retrieval. First, we use angle gradient to extract contour’s critical points, this is a simple approach which decrease the computational cost while retain spatial information of shapes. Second, we present a pairwise similarity measure, which is a quadratic assignment problem. This problem is approximately solved by spectral technique. This method is tested on standard MPEG-7 shape database using the standard performance evaluation scheme. The experimental results indicate that the proposed method outperforms the closely relate method.