Presentation 2012-03-28
Content Based Image Retrieval using Pules Coupled Neural Netowrks
Masato YONEKAWA, Hiroaki KUROKAWA,
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Abstract(in English) A Pulse Coupled Neural Network (PCNN) is a neural network composed of neurons firing in discretetime and those connections. The image processing using the PCNN has been proposed in many studies. Aligned the PCNN's neurons in two dimensional are associated an image's pixels for the image processing. The PCNN-Icon is a time series of a number of firing neurons. PCNN-Icons that are information of neurons firing pattern is used the image matching by comparing those similarity. We proposed the parameter adaptaion method for the image matching using the PCNN. Image matching using the PCNN can show good recognition rate with this parameter adaptation method. On the other hand, because of the retrieval for huge amount of digital image data, the Content Based Image Retrieval(CBIR) has been interest in recent years. Similarity of PCNN-Icons should be able to applicate for CBIR. In this study, We applied the image matching using PCNN to the CBIR. An efficiency of proposed method for CBIR was shown in the simulation results.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Pulse Coupled Neural Network / Content Based Image Retrieval
Paper # NLP2011-151
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Conference Information
Committee NLP
Conference Date 2012/3/20(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Content Based Image Retrieval using Pules Coupled Neural Netowrks
Sub Title (in English)
Keyword(1) Pulse Coupled Neural Network
Keyword(2) Content Based Image Retrieval
1st Author's Name Masato YONEKAWA
1st Author's Affiliation Tokyo University of Technology()
2nd Author's Name Hiroaki KUROKAWA
2nd Author's Affiliation Tokyo University of Technology
Date 2012-03-28
Paper # NLP2011-151
Volume (vol) vol.111
Number (no) 498
Page pp.pp.-
#Pages 6
Date of Issue