To visualize the volume data acquired from computation or sampling, it is necessary to estimate normals at the points corresponding to object surfaces. Volume data does not holds the geometric information for the surface comprising points, so it is necessary to calculate normals using local information at each point. The existing normal estimation methods have some problems of estimating incorrect normals at discontinuous, aliased or noisy points. Yagel et al. (1992) solved some of these problems using their context-sensitive method. However, this method requires too much processing time and it loses some information on detailed parts of the object surfaces. This paper proposes the surface-characteristic-sensitive normal estimation method which applies different operators according to characteristics of each surface for the normal calculation. This method has the same advantages of the context-sensitive method, and also some other advantages such as less processing time and the reduction of the information loss on detailed parts.
['Byeong Seok Shin', 'Yeong Gil Shin']
Fast normal estimation using surface characteristics