DocumentCode :
1601622
Title :
An Improved Threshold Selection Algorithm Based on Particle Swarm Optimization for Image Segmentation
Author :
Wei, Kaiping ; Zhang, Tao ; Shen, Xianjun ; Liu, Jingnan
Author_Institution :
Wuhan Univ., Wuhan
Volume :
5
fYear :
2007
Firstpage :
591
Lastpage :
594
Abstract :
This paper proposes an effective threshold selection method of image segmentation based on particle swarm optimization (PSO), which is embedded into two-dimensional Otsu algorithm. Traditional image segmentation methods are time-consuming computation and become an obstacle in real time application systems. In this paper, the threshold selection approach based on PSO is proposed to deal with threshold selection of image segmentation. The threshold is obtained through PSO. PSO is realized successfully in the process of solving the threshold selection problem. The experiments of segmenting images are illustrated to show that the proposed method can get ideal segmentation result with less computation cost.
Keywords :
image segmentation; particle swarm optimisation; image segmentation; improved threshold selection algorithm; particle swarm optimization; real time application systems; Application software; Computational efficiency; Computer science; Global Positioning System; Histograms; Image segmentation; Particle swarm optimization; Pixel; Real time systems; Two dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.226
Filename :
4344908
Link To Document :
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