Fuzzy clustering image segmentation based on particle swarm optimization

被引：0
作者：
Feng, Zhanshen [1 ]
Zhang, Boping [1 ]
机构：
[1] Department of Information Engineering, Xu Chang University, Xu Chang, Henan
来源：
Telkomnika (Telecommunication Computing Electronics and Control) | 2015年 / 13卷 / 01期
关键词：
Fuzzy clustering; Image segmentation; Particle swarm optimization;
D O I：
10.12928/TELKOMNIKA.v13i1.1269
中图分类号：
学科分类号：
摘要：
Image segmentation refers to the technology to segment the image into different regions with different characteristics and to extract useful objectives, and it is a key step from image processing to image analysis. Based on the comprehensive study of image segmentation technology, this paper analyzes the advantages and disadvantages of the existing fuzzy clustering algorithms; integrates the particle swarm optimization (PSO) with the characteristics of global optimization and rapid convergence and fuzzy clustering (FC) algorithm with fuzzy clustering effects starting from the perspective of particle swarm and fuzzy membership restrictions and gets a PSO-FC image segmentation algorithm so as to effectively avoid being trapped into the local optimum and improve the stability and reliability of clustering algorithm. The experimental results show that this new PSO-FC algorithm has excellent image segmentation effects.
引用
收藏
页码：128 / 136
页数：8
相关论文
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