By Topic

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

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Dongming Zhao ; Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA ; Xintong Zhang

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

Published in:

Image Processing, IEEE Transactions on  (Volume:6 ,  Issue: 6 )