Texture segmentation using intensified fuzzy kohonen clustering network

Authors:
Dong Liu;Yinggan Tang;Xinping Guan
Affiliations:
Institute of Electrical Engineering, Yanshan University, Qinhuangdao, P.R. China;Institute of Electrical Engineering, Yanshan University, Qinhuangdao, P.R. China;Institute of Electrical Engineering, Yanshan University, Qinhuangdao, P.R. China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

Citing 2
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Abstract

Fuzzy Kohonen clustering network(FKCN) shows great superiority in processing the clustering in image segmentation. In this paper, an intensified Fuzzy Kohonen clustering Network (IFKCN) is proposed for texture segmentation. The method adjusts fuzzy factors to accelerate the speed of convergence. It intensifies the biggest membership and suppresses the other. By using this network in Brodatz texture segmentation, its iteration is fewer and the speed of convergence is quicker than FKCN and AFKCN(Adaptive Fuzzy Kononen clustering Network), and segmentation results are as well as FKCN.