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Proceedings Paper

A self-adaptive ant colony optimization approach for image segmentation
Author(s): Jue Lu
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Paper Abstract

Ant colony optimization, with good discretion, parallel, robustness and positive feedback, is well suited to image segmentation. But its search is random and has much computation for convergence. Constant evaporating coefficient leads to early convergence or stagnation. To improve it, the ideal of setting primary cluster center is proposed. Meanwhile, the algorithm is implemented in a small window so as to reduce its computation. The evaporating coefficient is also set to change with the number of ants which pass the allowable path in order to keep its good global convergence and stability. This method can segment an image accurately. Experimental results show it's an effective approach.

Paper Details

Date Published: 4 January 2006
PDF: 6 pages
Proc. SPIE 5985, International Conference on Space Information Technology, 59853F (4 January 2006); doi: 10.1117/12.657993
Show Author Affiliations
Jue Lu, Wuhan Univ. of Technology (China)


Published in SPIE Proceedings Vol. 5985:
International Conference on Space Information Technology
Cheng Wang; Shan Zhong; Xiulin Hu, Editor(s)

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