DocumentCode :
3329036
Title :
A multilayer cooperative/competitive method for creating hierarchical structures by clustering maximally-related nodes
Author :
Maren, A.J. ; Minsky, V. ; Ali, M.
Author_Institution :
Space Inst., Tennessee Univ., Tullahoma, TN, USA
fYear :
1988
fDate :
24-27 July 1988
Firstpage :
95
Abstract :
A cooperative/competitive method can be used to generate hierarchical structures for clustering problems. These structures can prove useful in achieving high-level machine vision goals such as scene analysis through perceptual organization. The cooperative/competitive method was specifically designed for clustering related image segments to create hierarchical scene structures. The method addresses the need for rapid extraction of clusters from large sets of regions with different inter-region relationships. The multiple relationships cooperate to form clusters from the input nodes. These clusters then compete, eliminating all but the strongest. The input nodes that comprise the surviving clusters are combined. This process is applied repeatedly to produce a full hierarchical structure. A specific example uses this approach to create a hierarchical structure from a synthetic segmented image.<>
Keywords :
computer vision; clustering; computer vision; hierarchical structures; high-level machine vision; image segments; maximally-related nodes; multilayer cooperative/competitive method; perceptual organization; scene analysis; Machine vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1988., IEEE International Conference on
Conference_Location :
San Diego, CA, USA
Type :
conf
DOI :
10.1109/ICNN.1988.23917
Filename :
23917
Link To Document :
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