Presentation | 2013-05-27 A study on the image feature extraction method by the IC-PCNN Yuta ISHIDA, Hiroaki KUROKAWA, |
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Abstract(in English) | The Pulse Coupled Neural Network(PCNN) is a neural network model that consists of spiking neurons. The PCNN has been applied to a lot of image processing, and the image matching is one of the successful application of the PCNN. In the image matching method using PCNN, the "PCNN Icon" that defined from the dynamics of the PCNN is used as a kind of the image feature value. This image matching technique is applied to a method for the content base image retrieval system. However, due to the structure of the PCNN, only the gray-scaled image is used in the PCNN, i.e., the color information of the image will be lost in the case of using color images. In this study, we propose the method of the image feature extraction using the Inhibitory connected PCNN(IC-PCNN) and applied to the image matching method. Where the IC-PCNN is an extended model of the PCNN for the color image processing without the loss of color information. We propose the method of using IC-PCNN. In the simulation, we show the results of the image matching using the color image database. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Inhibitory Connected Pulse Coupled Neural Network / Image matching |
Paper # | NLP2013-15 |
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Conference Information | |
Committee | NLP |
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Conference Date | 2013/5/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A study on the image feature extraction method by the IC-PCNN |
Sub Title (in English) | |
Keyword(1) | Inhibitory Connected Pulse Coupled Neural Network |
Keyword(2) | Image matching |
1st Author's Name | Yuta ISHIDA |
1st Author's Affiliation | Tokyo University of Technology() |
2nd Author's Name | Hiroaki KUROKAWA |
2nd Author's Affiliation | Tokyo University of Technology |
Date | 2013-05-27 |
Paper # | NLP2013-15 |
Volume (vol) | vol.113 |
Number (no) | 69 |
Page | pp.pp.- |
#Pages | 5 |
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