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ASME Press Select Proceedings
International Conference on Electronics, Information and Communication Engineering (EICE 2012)Available to Purchase
By
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859971
No. of Pages:
1008
Publisher:
ASME Press
Publication date:
2012

A new algorithm for image segmentation based on k-mean and particle swarm optimization algorithm is proposed in the paper. K-mean clustering algorithm is a local search algorithm because it is easily trapped local optimum and is sensitive to initial value effectively. On the other hand, particle swarm optimization algorithm is a global optimization algorithm. By incorporating the local search ability of k-mean algorithm and the global optimization ability of PSO and taking the criterion function of k-mean as the object function of PSO, a new hybrid color image segmentation algorithm based on particle swarm optimization and k-mean algorithm is proposed. Experiments show that the new algorithm can get the optimal quantizated image by PSNR and RMSE.

Abstract
Keywords
Introduction
K-Means Clustering
PSO Based on K-Means
The Present Algorithm:
Experimental Results
Conclusion
Acknowledgment
References
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