NDLI: Contactless Palm Vein Recognition Using a Mutual Foreground-Based Local Binary Pattern

Content Provider	IEEE Xplore Digital Library
Author	Wenxiong Kang Qiuxia Wu
Copyright Year	2005
Abstract	Local binary pattern (LBP) is popular for the texture representation owing to its discrimination ability and computational efficiency, but when used to describe the sparse texture in palm vein images, the discrimination ability is diluted, leading to lower performance, especially for contactless palm vein matching. In this paper, an improved mutual foreground LBP method is presented for achieving a better matching performance for contactless palm vein recognition. First, the normalized gradient-based maximal principal curvature algorithm and k -means method are utilized for texture extraction, which can effectively suppress noise and improve accuracy and robustness. Then, an LBP matching strategy was adopted for similarity measurements on the basis of extracted palm veins and their neighborhoods, which include the vast majority of useful distinctive information for identification while eliminating interference by excluding the background. To further improve the LBP performance, the matched pixel ratio was adopted to determine the best matching region (BMR). Finally, the matching score obtained in the process of finding the BMR was fused with results of LBP matching at the score level to further improve the identification performance. A series of rigorous contrast experiments using the palm vein data set in the CASIA multispectral palmprint image database were conducted. The obtained low equal error rate (0.267%) and comparisons with the most state-of-the-art approaches demonstrate that our method is feasible and effective for contactless palm vein recognition.
Sponsorship	IEEE Signal Processing Society
Starting Page	1974
Ending Page	1985
Page Count	12
File Size	2635057
File Format	PDF
ISSN	15566013
Volume Number	9
Issue Number	11
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Veins Feature extraction Pattern matching Thumb Iris recognition Image segmentation matched pixel ratio Biometrics palm vein recognition local binary pattern mutual foreground principal curvatures
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Safety, Risk, Reliability and Quality

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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