Chun-Yen Chen1,2, Kuo-Young Cheng1,2, Hong-Yuan Mark Liao1
1. Institute of Information Science, Academia Sinica.
2. Department of Computer Science and Information Engineering, National Taiwan University.
e-mail: email@example.com; firstname.lastname@example.org; email@example.com
Design of an anisotropic diffusion-based filter that performs Bayesian classification for automatic selection of a proper weight for fairing polygon meshes is proposed. The data analysis based on Bayesian classification is adopted to determine the decision boundary for separating potential edge and non-edge vertices in the curvature space. The adaptive diffusion filter is governed by a double-degenerate anisotropic equation that determines how each polygon vertex is moved along its normal direction in the curvature space iteratively until a steady state is reached. The determination of how much a polygon vertex should be moved depends on whether it is a potential edge or a non-edge vertex. At each fairing step, conceptually, a bi-directional curvature map whose boundary line while couched by the weight value can be plotted to understand the type of a vertex. Experimental results show that the proposed diffusion-based approach could effectively smooth out noises while retaining useful data to a very good degree.