DocumentCode :
3480794
Title :
Image segmentation based on improved PSO
Author :
Hongmei, Tang ; Cuixia, Wu ; Liying, Han ; Xia, Wang
Author_Institution :
Sch. of Inf. Eng., Hebei Univ. of Technol., Tianjin, China
Volume :
3
fYear :
2010
fDate :
12-13 June 2010
Firstpage :
191
Lastpage :
194
Abstract :
The multilevel thresholds image segmentation method based on maximum entropy and improved particle swarm optimization (PSO) is presented in this paper. The proposed algorithm takes advantage of the characteristics of particle swarm optimization, and improves the parameter and evolutional process of basic PSO. Compared with the basic PSO method, the proposed method can get the better optimal thresholds and more ideal segmentation result with less computation cost and has good search stability in the experiments. The experimental results indicate that the proposed method is an promising and efficient segmentation method with fast convergence and high computational efficiency.
Keywords :
convergence; entropy; image segmentation; particle swarm optimisation; PSO; convergence; image segmentation; maximum entropy; particle swarm optimization; Histograms; Image segmentation; image segmentation; maximum entropy; multilevel threshold; particle swarm optimization(PSO);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6944-4
Type :
conf
DOI :
10.1109/CCTAE.2010.5544490
Filename :
5544490
Link To Document :
بازگشت