A Clustering Method for Segmentation of All Circumferential Range Image

Abstract

In this paper, a clustering method is proposed to segment all circumferential range image , which is employed as preprocessing of 3-D shapes modeling for the object that has arbitrary topology. The proposed method performs the image segmentation that the range data points are classified into domains with similar quadric surfaces. In order to determine the desirable clusters, this method consists of two stages. First, New clusters are created on demand with learning the range data in recursive form (Stage 1). However, a number of wrong clusters are created. In next stage, after dispensable clusters are vanished by the competition of clusters, remaining clusters are gradually agglomerated (Stage 2). Consequently, since the only appropriate clusters are left, the image segmentation can be performed by assigning the data to these clusters.