Content-based shape retrieval using different shape descriptors: a comparative study

Abstract

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 several shape descriptors which have been widely adopted for CBIR, they are: Fourier descriptors (FD), curvature scale space (CSS) descriptors (CSSD), Zernike moment descriptors (ZMD) and grid descriptors (GD). The strengths and limitations of these methods are analyzed and clarified. Retrieval results are given to show the comparison.