Performance evaluation of high frequency sub-bands of wavelet transform for palmprint recognition

ZHANG Kai-lin¹, ZHANG Yan-qiang²

(1.Dept. of Information Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China;ª¤2.Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China)ª¤ª¤ª¤;1.Dept.of Information Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China;2.Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China



Abstract:

Wavelet decomposition has been applied in palmprint recognition successfully. However, only the low frequency sub-band was used for further feature extraction, while the high frequency sub-bands were considered to be unsuitable for palmprint recognition due to their sensitivity to noise and shape distortion. In this paper, we firstly investigate the performances of all the sub-bands by using principal component analysis (PCA) on the BJTU and PolyU palmprint databases, and then use mean filtering to enhance the robustness of the high frequency sub-bands. We find that the preprocessed high frequency sub-bands not only can be used for palmprint recognition but also contain complementary information with the low frequency sub-band. The experimental results show that the performances of the horizontal and vertical high frequency sub-bands can be promoted up to a competitive level, and the fusion scheme, which combines the matching scores of high frequency sub-bands with that of low frequency sub-band, is superior to the conventional recognition methods.ª¤

Key words:  palmprint recognition  wavelet transform  principal component analysis (PCA)  matching score fusionª¤

DOI£º10.11916/j.issn.1005-9113.2012.06.020

Clc Number:TP391.4

Fund: