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Authors: Haichao Liang and Takashi Morie

Affiliation: Kyushu Institute of Technology, Japan

Abstract: We propose a model of coarse edge detection using self-adjusting resistive-fuse networks. The resistive-fuse network model is known as a nonlinear image processing model, which can detect coarse edges from images by smoothing noise and small regions. However, this model is hardly used in real environment because of the sensitive dependence on the parameters and the complexity of the annealing process. In this paper, we first introduce self-adjusting parameters to reduce the number of parameters to be controlled. Then, we propose a heating-and-cooling sequence for fast and robust edge detection. The proposed model can detect edges more correctly than the original one, even if an input image includes a gradation.

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Paper citation in several formats:
Liang, H. and Morie, T. (2010). Coarse Image Edge Detection using Self-adjusting Resistive-fuse Networks. In Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems (ICEIS 2010) - PRIS; ISBN 978-989-8425-14-0, SciTePress, pages 43-52. DOI: 10.5220/0003015600430052

@conference{pris10,
author={Haichao Liang. and Takashi Morie.},
title={Coarse Image Edge Detection using Self-adjusting Resistive-fuse Networks},
booktitle={Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems (ICEIS 2010) - PRIS},
year={2010},
pages={43-52},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003015600430052},
isbn={978-989-8425-14-0},
}

TY - CONF

JO - Proceedings of the 10th International Workshop on Pattern Recognition in Information Systems (ICEIS 2010) - PRIS
TI - Coarse Image Edge Detection using Self-adjusting Resistive-fuse Networks
SN - 978-989-8425-14-0
AU - Liang, H.
AU - Morie, T.
PY - 2010
SP - 43
EP - 52
DO - 10.5220/0003015600430052
PB - SciTePress