Content-Based Shape Retrieval Using Different Affine Shape Descriptors

Shape representation is a fundamental issue in the newly emerging multimedia applications. In the Content Based Image Retrieval (CBIR), shape is an important low level image feature. Many shape representations have been proposed. However, for CBIR, a shape representation should satisfy several properties such as affine invariance, robustness, compactness, low computation complexity and perceptual similarity measurement. Against these properties, in this paper we attempt to study and compare three shape descriptors: two issued from Fourier method and the Affine Curvature Scale Space Descriptor (ACSSD). We build a retrieval framework to compare shape retrieval performance in terms of robustness and retrieval performance. The retrieval performance of the different descriptors is compared using two standard shape databases. Retrieval results are given to show the comparison.