DocumentCode :
314359
Title :
Range image segmentation using an oscillatory network
Author :
Liu, Xiuwen ; Wang, DeLiang
Author_Institution :
Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA
Volume :
3
fYear :
1997
fDate :
9-12 Jun 1997
Firstpage :
1656
Abstract :
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
Keywords :
feature extraction; image segmentation; least squares approximations; neural nets; parameter estimation; excitatory lateral connections; feature vectors; locally excitatory globally inhibitory oscillator network; range image segmentation; Clustering algorithms; Cognitive science; Computer networks; Image segmentation; Information science; Inhibitors; Local oscillators; Neural networks; Organizing; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
Type :
conf
DOI :
10.1109/ICNN.1997.614143
Filename :
614143
Link To Document :
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