Using multi-objective optimization PSO in SVM for fingerprint recognition

被引：0

作者：

机构：

[1] Department of Electrical Engineering, Tamkang University Taipei Country

来源：

Hsieh, C.-T. | 1600年 / Asian Network for Scientific Information卷 / 13期

关键词：

Fingerprint recognition; MOPSO-CD; SVM;

D O I：

10.3923/jas.2013.3705.3711

中图分类号：

学科分类号：

摘要：

The problem of fingerprint classification is discussed for many years. Support Vector Machine (SVM) is a traditional artificial intelligence algorithm developed for dealing classification problems. In this study, have used the core idea of multi-objective optimization to transform SVM into anew form. This form of SVM could help to solve the situation: In tradition, SVM is usually a single optimization equation andparameters for this algorithm can only be determined by user's experience, such as penalty parameter. Therefore, this algorithm is developed to help user prevent from suffering to use this algorithm in the above condition. It is has successfully proved that user do not need to make experiment to determine the penalty parameter C. NIST-4 database is used to assess the proposed algorithm. The experiment results show the method can get good classification results. © 2013 Asian Network for Scientific Information.

引用

页码：3705 / 3711

页数：6

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