Research on Improved PSO Algorithm Based on Contour Detection

Article Preview

Abstract:

In this paper, an improved PSO algorithm in unimodal, multimodal function can adapt quickly converges to a smaller fitness value. It’s suitable for complex non-linear environment. Combined with the adjusted Snake model can better convergence at the edge of the recess. Compared with other contour detection algorithms, this algorithm has better noise robustness, contour convergence accurate and efficient accuracy and efficiency.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

903-907

Citation:

Online since:

September 2014

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] LIANG Ying-hong. Human detection method in infrared video images[J]. Infrared and Laser Engineering, 2009, 38(5) , pp.931-935.

Google Scholar

[2] LIU Fu qiang; QIAN Jian sheng; WANG Xin hong, et al. Automatic separation of waste rock in coal mine based on image procession and recognition[J]. Journal of China Coal Society, 2000, pp.534-537.

Google Scholar

[3] Sun Jiping. Networking technology for safety supervision system in a coal mine[J]. Journal of China Coal Society, 2009, 34(11) , p.1547–1549.

Google Scholar

[4] Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks[C], Piscataway : IEEE Service Center, 1995, p.1942-(1948).

Google Scholar

[5] JIANG Nan; ZHANG Chun-sen. Application of genetic algorithm in image matching[J]. Infrared and Laser Engineering, 2008, 37, pp.324-327.

Google Scholar

[6] LI Heng; HAN Yan-li; YANG Fan. Method of ir offing ship target segmentation based on genetic algorithm[J]. Infrared and Laser Engineering, 2006, 35, pp.43-47.

Google Scholar

[7] A. Chatterjee and P. Siarry. Nonlinear Inertia Weight Variation for Dynamic Adaptation in Particle Swarm Optimization[J]. Computers & Operations Research, 2006, 33(3) , pp.859-871.

DOI: 10.1016/j.cor.2004.08.012

Google Scholar