Presentation 2011-01-24
Dependence of input image on color image segmentation using Inhibitory Connected Pulse Coupled Neural Network
Masahiro YOSHIHARA, Masato YONEKAWA, Hiroaki KUROKAWA,
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Abstract(in English) The image segementation is effective technic to extract objects from an image. In conventional method, initialization that depends on the input image's feature is necessary to the image segmentation. Initialization as well as conventional method is unnecessary for image segmentation using Pulse Coupled Neural Network(PCNN). We had proposed the Inhibitory Connected PCNN(IC-PCNN) as the extended PCNN model for color image processing. Also, in our previous study, We showed that the optimization of inhibitory connections lead to the accarate color image segmentation using IC-PCNN. However, the optimization of inhibitory connections that depend on the image is required for color image segmentation using IC-PCNN due to optimum condition of inhibitory connections deffer with the input image's color. In this papar, we show the influence of the parameter on dependence of color image segmentation using IC-PCNN on the input image's feature. From the simulation results, we show that the parameter search valid to reduce dependence of color image segmentation using IC-PCNN on the input image.
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Keyword(in English) image segmentation / inhibitory connected pulse coupled neural network
Paper # NLP2010-128,NC2010-92
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Conference Information
Committee NC
Conference Date 2011/1/17(1days)
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Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Dependence of input image on color image segmentation using Inhibitory Connected Pulse Coupled Neural Network
Sub Title (in English)
Keyword(1) image segmentation
Keyword(2) inhibitory connected pulse coupled neural network
1st Author's Name Masahiro YOSHIHARA
1st Author's Affiliation School of Computer Science, Tokyo University of Technology()
2nd Author's Name Masato YONEKAWA
2nd Author's Affiliation School of Computer Science, Tokyo University of Technology
3rd Author's Name Hiroaki KUROKAWA
3rd Author's Affiliation School of Computer Science, Tokyo University of Technology
Date 2011-01-24
Paper # NLP2010-128,NC2010-92
Volume (vol) vol.110
Number (no) 388
Page pp.pp.-
#Pages 6
Date of Issue