Application of Particle Swarm Optimization to pattern identification

被引：0
|
作者：
Zhang Ying [1 ]
Chen Xuebo [1 ]
Wu Qinghong [1 ]
Wang Wei [1 ]
机构：
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116024, Peoples R China
来源：
PROCEEDINGS OF THE 24TH CHINESE CONTROL CONFERENCE, VOLS 1 AND 2 | 2005年
关键词：
pattern identification; PSO; binarization; thinning;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new algorithm for supervised pattern identification based on Particle Swarm Optimization (PSO) is proposed in this paper. At first, an image database with training image samples is set up. Secondly, image samples to be identified and stored in the database are preprocessed. Then, point matching is made between the identified images after preprocessing with the training images after preprocessing by using PSO, respectively. Finally, the identification is realized by seeking the minimum of a defined classification function. This algorithm is approved to be effective, accurate and simple by the experiments.
引用
收藏
页码：1752 / 1754
页数：3
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