Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/7827
Title: Wavelet energy feature extraction and matching for palmprint recognition
Authors: Wu, XQ
Wang, KQ
Zhang, D 
Keywords: Biometrics
Palmprint recognition
Wavelet energy feature
Weighted city block distance
Issue Date: 2005
Source: Journal of computer science and technology, 2005, v. 20, no. 3, p. 411-418 How to cite?
Journal: Journal of Computer Science and Technology 
Abstract: According to the fact that the basic features of a palmprint, including principal lines, wrinkles and ridges, have different resolutions, in this paper we analyze palmprints using a multi-resolution method and define a novel palmprint feature, which called wavelet energy feature (WEF), based on the wavelet transform. WEF can reflect the wavelet energy distribution of the principal lines, wrinkles and ridges in different directions at different resolutions (scales), thus it can efficiently characterize palmprints. This paper also analyses the discriminabilities of each level WEF and, according to these discriminabilities, chooses a suitable weight for each level to compute the weighted city block distance for recognition. The experimental results show that the order of the discriminabilities of each level WEF, from strong to weak, is the 4th, 3rd, 5th, 2nd and 1st level. It also shows that WEF is robust to some extent in rotation and translation of the images. Accuracies of 99.24% and 99.45% have been obtained in palmprint verification and palmprint identification, respectively. These results demonstrate the power of the proposed approach.
URI: http://hdl.handle.net/10397/7827
ISSN: 1000-9000
DOI: 10.1007/s11390-005-0411-8
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

39
Last Week
0
Last month
0
Citations as of Sep 11, 2017

WEB OF SCIENCETM
Citations

27
Last Week
0
Last month
0
Citations as of Sep 22, 2017

Page view(s)

58
Last Week
4
Last month
Checked on Sep 24, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.