An adaptive image segmentation method based on a modified pulse coupled neural network

Authors:
Min Li;Wei Cai;Xiao-yan Li
Affiliations:
Xi'an Research Inst. of Hi-Tech Hongqing Town, Shaanxi Province, P.R.C.;Xi'an Research Inst. of Hi-Tech Hongqing Town, Shaanxi Province, P.R.C.;Academy of Armored Force Engineering Department of Information Engineering, Beijing, P.R.C.
Venue:
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Year:
2006

Citing 2
Cited 2

Feature linking via synchronization among distributed assemblies: Simulations of results from cat visual cortex

Neural Computation
Perfect image segmentation using pulse coupled neural networks

IEEE Transactions on Neural Networks

Review article: Review of pulse-coupled neural networks

Image and Vision Computing
An Iterative Thresholding Segmentation Model Using a Modified Pulse Coupled Neural Network

Neural Processing Letters

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Abstract

Pulse-coupled neural network (PCNN) based on Eckhorn's model of the cat visual cortex has great significant advantage in image segmentation. However, the segmented performance depends on the suitable PCNN parameters, which are tuned by trial so far. Focusing on the famous difficult problem of PCNN, this paper establishes a modified PCNN, and proposes adaptive PCNN parameters determination algorithm based on water region area. Experimental results on image segmentation demonstrate its validity and robustness.