Content-based 3D retrieval by Krawtchouk moments

With the rapid increase of available 3D models, content-based 3D retrieval is attracting more and more research interests. One of the key problems in content-based 3D retrieval is to extract discriminative features for measuring the similarity and dissimilarity between different shapes. In this paper, we define 3D Krawtchouk moments for 3D shape analysis and retrieval. Differing with 3D Zernike moments deduced from continuous orthogonal polynomials, the basis of 3D Krawtchouk moments is discrete orthogonal polynomial. It has some interesting property for describing shape information and retrieving 3D models, such as multi-resolution, high-computation, simplification and so on. To verify the advantage of 3D Krawtchouk moments, experiments are carried out to compare the retrieving performance based on Krawtchouk moments and Zernike moments. The results have proven that Krawtchouk moments can achieve better retrieving accuracy and efficiency.