Palmprint Recognition Based on RB K-means and Hierarchical SVM

Author

Wu, Yi-pu ; Tian, Jian-Wu ; Xu, Dan ; Zhang, Xue-Jie

Author_Institution

Yunnan Univ., Kunming

Volume

6

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3641

Lastpage

3647

Abstract

In this paper, we present a novel recognition algorithm which is based on RB K-means and Hierarchical SVM (Support Vector Machines). Firstly, we pre-classify imposter samples by RB K-means. Secondly, the Linear SVM is applied to the primary classification. Finally, we use the Non-linear SVM for the classification. Our experiment demonstrates that our algorithm with RBF kernel is feasible and effective in terms of FRR and FAR (FRR:0.242%, FAR:2.668%) on our palmprint database.

Keywords

biometrics (access control); image recognition; pattern classification; radial basis function networks; support vector machines; classification; hierarchical support vector machine; nonlinear support vector machine; palmprint recognition algorithm; radial basis K-means; radial basis function network kernel; Biometrics; Computer science; Cybernetics; Fingerprint recognition; Kernel; Machine learning; Machine learning algorithms; Nonlinear equations; Support vector machine classification; Support vector machines; Fourier transform; Palmprint Recognition; RB K-means; SVM;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370778

Filename

4370778