Presentation 2009-08-04
Multi-Scaling of Gray Level Image and its Dynamic Image Segmentation Using Discrete-time Dynamical Systems
Ken'ichi FUJIMOTO, Mio MUSASHI, Tetsuya YOSHINAGA,
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Abstract(in English) The authors have proposed a discrete-time coupled system consisting of chaotic neurons and a global inhibitor. We demonstrated that by arranging adequate couplings between adjacent chaotic neurons, it works well as a dynamic image segmentation system for a binary image. In this paper, we improve our system so that it can work for a gray level image. In segmentation of a gray level image, to find an image region with different gray levels is fundamental. As a pre-processing of our system, we consider using a multi-scaling system, which consists of a discrete-time dynamical system, for gray levels. The system can concurrently compute whether adjacent pixels with different gray levels are coupled. We demonstrate that the combined system consisting of the two discrete-time dynamical systems works well to an example that dynamically segments a gray level image.
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Keyword(in English) coupled chaotic neurons / gray level image / multi-scaling of gray levels / dynamic image segmentation
Paper # NLP2009-53
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Conference Information
Committee NLP
Conference Date 2009/7/27(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) Multi-Scaling of Gray Level Image and its Dynamic Image Segmentation Using Discrete-time Dynamical Systems
Sub Title (in English)
Keyword(1) coupled chaotic neurons
Keyword(2) gray level image
Keyword(3) multi-scaling of gray levels
Keyword(4) dynamic image segmentation
1st Author's Name Ken'ichi FUJIMOTO
1st Author's Affiliation Institute of Health Biosciences, The University of Tokushima()
2nd Author's Name Mio MUSASHI
2nd Author's Affiliation Graduate School of Health Sciences, The University of Tokushima
3rd Author's Name Tetsuya YOSHINAGA
3rd Author's Affiliation Institute of Health Biosciences, The University of Tokushima
Date 2009-08-04
Paper # NLP2009-53
Volume (vol) vol.109
Number (no) 167
Page pp.pp.-
#Pages 4
Date of Issue