Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33746
Title: Feature band selection for multispectral palmprint recognition
Authors: Guo, Z
Zhang, L 
Zhang, D 
Keywords: (2D)2PCA
Biometrics
Multispectral
Palmprint recognition
Issue Date: 2010
Source: Proceedings - International Conference on Pattern Recognition, 2010, p. 1136-1139 How to cite?
Journal: Proceedings - International Conference on Pattern Recognition 
Abstract: Palmprint is a unique and reliable biometric characteristic with high usability. Many palmprint recognition algorithms and systems have been successfully developed in the past decades. Most of the previous works use the white light sources for illumination. Recently, it has been attracting much research attention on developing new biometric systems with both high accuracy and high anti-spoof capability. Multispectral palmprint imaging and recognition can be a potential solution to such systems because it can acquire more discriminative information for personal identity recognition. One crucial step in developing such systems is how to determine the minimal number of spectral bands and select the most representative bands to build the multispectral imaging system. This paper presents preliminary studies on feature band selection by analyzing hyperspectral palmprint data (420nm-1100nm). Our experiments showed that 2 spectral bands at 700nm and 960nm could provide most discriminate information of palmprint. This finding could be used as the guidance for designing multispectral palmprint systems in the future.
Description: 2010 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, 23-26 August 2010
URI: http://hdl.handle.net/10397/33746
ISBN: 9780769541099
ISSN: 1051-4651
DOI: 10.1109/ICPR.2010.284
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