DocumentCode :
3218589
Title :
Automatic Threshold Selection Based on Particle Swarm Optimization Algorithm
Author :
Zhiwei Ye ; Hongwei Chen ; Wei Liu ; JinPing Zhang
Author_Institution :
Sch. of Comput. Sci., Hubei Univ. of Technol., Wuhan
Volume :
1
fYear :
2008
fDate :
20-22 Oct. 2008
Firstpage :
36
Lastpage :
39
Abstract :
Image segmentation is a long-term difficult problem, which hasnpsilat been fully solved. Thresholding is one of the most popular algorithms. Particle swarm optimization (PSO) was recently proposed algorithm, which has been successfully applied to solve many optimization problems. Based on the analysis of Otsu threshold selection can be viewed as a continuous optimization problem. Thus, a new method to select image threshold automatically based on PSO algorithm is employed in the paper. The performance of this algorithm is compared with Otsu, and experimental results show that PSO algorithm can reveal very encouraging results in terms of the quality of solution found and the processing time required.
Keywords :
image segmentation; particle swarm optimisation; Otsu threshold selection; automatic image threshold selection; continuous optimization problem; image segmentation; particle swarm optimization algorithm; Automation; Birds; Computer science; Educational institutions; Genetic algorithms; Image segmentation; Marine animals; Organisms; Particle swarm optimization; Remote sensing; image segmentation threshold PSO;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-0-7695-3357-5
Type :
conf
DOI :
10.1109/ICICTA.2008.51
Filename :
4659438
Link To Document :
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