Cooperative active contour model and its application to remote sensing

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Cooperative active contour model and its application to remote sensing

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Symposium on Applied Computing archive
Proceedings of the 2006 ACM symposium on Applied computing table of contents

Dijon, France

SESSION: Poster papers table of contents

Pages: 44 - 45

Year of Publication: 2006

ISBN:1-59593-108-2

Authors

Noriko Matsumoto	Saitama University, Saitama, Japan
Norihiko Yoshida	Saitama University, Saitama, Japan
Shuji Narazaki	Nagasaki University, Nagasaki, Japan

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

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ABSTRACT

We propose a decentralized cooperative processing applied to the active contour model "Snake", which applies multiple Snakes to a single region, to improve its detection accuracy. We verify the effectiveness of our proposal in the cases of Multi-Snakes with different parameter sets and Multi-Snakes applied to RGB-decomposed images. We then apply it to multi-spectral remote sensing, and show that Multi-Snakes detected the boundary with enough accuracy.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	T. Wada, Y. Nomura and T. Matsuyama: "Cooperative Distributed Image Segmentation", IPSJ Journal, Vol.36, No.4, pp.879--891, April (1995).
	2	Song Chun Zhu , Alan Yuille, Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.18 n.9, p.884-900, September 1996 [doi>10.1109/34.537343 ]
	3	Y. Matsuzawa, T. Abe: "Region Extraction Using Competition of Multiple Active Contour Models", IEICE Transactions (D-II), Vol. J83-D-II, No.4, pp.1100--1109, April (2000).