Automatic threshold selection based on Particle Swarm Optimization algorithm

被引：14
|
作者：
Ye Zhiwei [1 ]
Chen Hongwei [1 ]
Liu Wei [1 ]
Zhang Jinping [2 ]
机构：
[1] Hubei Univ Technol, Sch Comp Sci, Wuhan 430068, Peoples R China
[2] Wuhan Univ, Sch Remote Sens & Informat Engn, Wuhan 430079, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL 1, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICICTA.2008.51
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Image segmentation is a long-term difficult problem, which hasn't been fully solved. Thresholding is one of the most popular algorithms. Particle Swarm Optimization (PSO) was recent v proposed algorithm, which has been successfully applied to solve many optimization problems. Based on the analysis of Otsu threshold selection can be viewed as a continuous optimization problem. Thus, a new method to select image threshold automatically based on PSO algorithm is employed in the paper. The performance of this algorithm is compared with Otsu, and experimental results show that PSO algorithm can reveal very encouraging results in terms of the quality of solution found and the processing time required.
引用
收藏
页码：36 / +
页数：2
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