IMPROVED 2D MAXIMUM ENTROPY THRESHOLD SEGMENTATION METHOD BASED ON PSO

Liping Zheng, Guangyao Li, Jing Liang, Quanke Pan

Abstract

Image segmentation plays an important role in the field of image processing. Threshold segmentation is a simple and important method in image segmentation. Maximum Entropy is a common threshold segmentation method. In order to adequately utilize gray information and spatial information of image, an improved 2D entropy computation method is proposed. Otherwise, Particle Swarm Optimization(PSO) algorithm is used to solve maximum of improved entropy. Maximum takes as the optimal image segmentation threshold. In this paper, two CT images were segmented in experiment. Experimental results show that this method can quickly and accurately obtain segmentation threshold. Otherwise, this method has strong anti-noise capability and save computation time.

References

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Paper Citation


in Harvard Style

Zheng L., Li G., Liang J. and Pan Q. (2009). IMPROVED 2D MAXIMUM ENTROPY THRESHOLD SEGMENTATION METHOD BASED ON PSO . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 287-291. DOI: 10.5220/0002314302870291


in Bibtex Style

@conference{icec09,
author={Liping Zheng and Guangyao Li and Jing Liang and Quanke Pan},
title={IMPROVED 2D MAXIMUM ENTROPY THRESHOLD SEGMENTATION METHOD BASED ON PSO },
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009)},
year={2009},
pages={287-291},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002314302870291},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICEC, (IJCCI 2009)
TI - IMPROVED 2D MAXIMUM ENTROPY THRESHOLD SEGMENTATION METHOD BASED ON PSO
SN - 978-989-674-014-6
AU - Zheng L.
AU - Li G.
AU - Liang J.
AU - Pan Q.
PY - 2009
SP - 287
EP - 291
DO - 10.5220/0002314302870291