DocumentCode :
2788025
Title :
Biometric identification based on low-quality hand vein pattern images
Author :
Zhao, Shi ; Wang, Yi-Ding ; Wang, Yun-Hong
Author_Institution :
Chinese Acad. of Sci., Beijing
Volume :
2
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
1172
Lastpage :
1177
Abstract :
Vein pattern is used as biometric feature in recent 20 years and It attracts much attention from 2000. A complete vein pattern recognition system contains three key procedures, vein image collection, vein pattern segment and feature extraction. In this paper, we adopt low-cost collection devices and discuss all the three parts in details. First a novel image collection way is proposed, which could enhance the contrast. Then a denoising algorithm using wavelets thresholding based on Besov norm regularization is discussed. This algorithm could remove the high noise while do not hurt the contrast. Finally, two novel robust features specially designed for vein pattern are put forward. Experimental results show that our system is as successful as traditional high-price system. In conclusion, our research makes using low-cost devices to recognize vein patterns possible.
Keywords :
biometrics (access control); feature extraction; image denoising; image segmentation; wavelet transforms; Besov norm regularization; biometric feature; biometric identification; denoising algorithm; feature extraction; hand vein pattern images; vein image collection; vein pattern recognition system; vein pattern segment; wavelets thresholding; Biometrics; Blood; Cameras; Cybernetics; Finite impulse response filter; Light scattering; Machine learning; Pattern recognition; Temperature; Veins; Besov space; Biometric; LBP; hand vein patterns; noise deduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620581
Filename :
4620581
Link To Document :
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