Gradient-based polyhedral segmentation for range images

A novel method is developed for robust polyhedral segmentation of 3-D range images. The method consists of three operations: (1) a two-dimensional gradient histogram space is generated based on gradients along directions of x- and y-coordinates; (2) a four-neighborhood iterative expanding algorithm is developed for region grouping according to a gradient feature space; (3) for noise and regions with geometrical distortion, a merge process is applied to the first-round segmentation results. The experiments show that the proposed algorithm generates good results for understanding polyhedral objects in range images. (C) 2003 Elsevier Science B.V. All rights reserved.