An Improved Threshold Selection Algorithm Based on Particle Swarm Optimization for Image Segmentation

Authors:
Kaiping Wei;Tao Zhang;Xianjun Shen;Jingnan Liu
Affiliations:
Wuhan University, China;Central China Normal University, China;Central China Normal University, China;Wuhan University, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 05
Year:
2007

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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.