The capacity and the versatility of the pulse coupled neural network in the image matching

Authors:
Yuta Ishida;Masato Yonekawa;Hiroaki Kurokawa
Affiliations:
School of Computer Science, Tokyo University of Technology, Hachioji, Tokyo, Japan;School of Computer Science, Tokyo University of Technology, Hachioji, Tokyo, Japan;School of Computer Science, Tokyo University of Technology, Hachioji, Tokyo, Japan
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

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Abstract

The image matching is an important technique in the image processing and the method using Pulse Coupled Neural Network (PCNN) had been proposed. One of the useful feature of the method is that the method is valid for the image matching among rotated, magnified and shrunk images. We have been proposed the parameter learning method of the PCNN for the image matching. Considering that the image matching technique will utilize for any advanced image processing such as a content based image retrieval, the capacity and the versatility of the method are important characteristics to evaluate the method. In this study, our method is tested using total 17,920 images and we describe the characteristics of the capacity and the versatility of image matching method using PCNN with our parameter learning algorithm.