Range-data-based object surface segmentation via edges and critical points

A novel method for range image segmentation is presented in this paper. It is based on an integration of edge and region information. The algorithm consists of three steps: edge and critical point detection, triangulation, and region growing. Experimental results show that the method is efficient for segmentation of the range images that contain polyhedral objects. A three-dimensional (3-D) surface structure graph (SSG) obtained from the segmentation is a description of the surface structure about an object. Therefore, a segmentation result also presents a data set that can be used to establish a surface model for computer-aided-design-based (CAD-based) vision and object recognition.