Multilevel thresholding method for image segmentation based on an adaptive particle swarm optimization algorithm

被引：0
|
作者：
Guo, Chonghui [1 ]
Li, Hong [1 ]
机构：
[1] Dalian Univ Technol, Inst Syst Engn, Dalian 116024, Peoples R China
来源：
AI 2007: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2007年 / 4830卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The multilevel thresholding method with maximum entropy is one of the most important image segmentation methods in image processing. However, its time-consuming computation is often an obstacle in real time application systems. Particle swarm optimization (PSO) algorithm is a class of heuristic global optimization algorithms which appeared recently. In this paper, the maximum entropy is obtained through an adaptive particle swarm optimization (APSO) algorithm. The APSO algorithm is shown to obtain the maximum entropy of multilevel thresholding effectively on experiments of image segmentation.
引用
收藏
页码：654 / 658
页数：5
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