By Topic

Range image segmentation using an oscillatory network

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)
Xiuwen Liu ; Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA ; DeLiang Wang

We use a locally excitatory globally inhibitory oscillator network (LEGION) as a framework for range image segmentation. Each oscillator in the LEGION network has excitatory lateral connections to the oscillators in its neighborhood as well as a connection with a global inhibitor. The lateral connection between two oscillators is established based on the similarity between their feature vectors which consist of the surface normal and curvature at the corresponding pixel locations. The emergent behavior of the LEGION network gives rise to the segmentation result. Unlike other methods, our scheme needs no assumption about the underlying structures in image data and no prior knowledge regarding the number of regions. Experimental results for real range images are presented

Published in:

Neural Networks,1997., International Conference on  (Volume:3 )

Date of Conference:

9-12 Jun 1997