Multilevel Thresholding Based on Exponent Gray Entropy and Niche Chaotic Particle Swarm Optimization

被引：0
|
作者：
Shen, Yi [1 ,2 ]
Wu, Yiquan [2 ]
Ji, Yang [2 ]
机构：
[1] Nanchang Hangkong Univ, Key Lab Nondestruct Testing, Minist Educ, Nanchang 330063, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Nanjing 210016, Peoples R China
来源：
FOUNDATIONS OF INTELLIGENT SYSTEMS (ISKE 2011) | 2011年 / 122卷
基金：
中国国家自然科学基金;
关键词：
threshold selection; exponent gray entropy; multi-threshold; chaotic mutation; niche particle swarm optimization;
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 method of threshold selection based on maximal Shannon entropy or exponent entropy only depend on the probability information from gray image histogram, and don't immediately consider the uniformity of the gray scale within the cluster. Considering these facts, thresholding based on exponent gray entropy is proposed. Firstly, exponent gray entropy is defined and the method of single threshold selection is given. Then, the method is extended to multilevel thresholding. Furthermore, the niche chaotic mutation particle swarm optimization algorithm is adopted to find the best multi-threshold. Many experimental results show that, compared with multilevel thresholding based on maximal entropy and particle swarm optimization, the proposed segmentation method has less operation times and segmented images of the suggested method are more accurate in edge and texture.
引用
收藏
页码：437 / +
页数：3
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