Abstract
As the identification technology is developed day by day, so is the counterfeit, and any accreditation system can be tricked. Therefore, a complete biometric identification system is supposed to distinguish between real and fake. Aiming at the liveness detection problems during the dorsal hand vein (DHV) recognition process, this paper proposes a method which combines principal component analysis and power spectrum estimation of the AR model together, three kinds of fake hand vein images which are paper printed, wearing thin rubber gloves and wearing thick rubber gloves have tested, and the result shows that the recognition rate of fake samples can reach 98.3 %, which proves that this method can realize in liveness detection of DHVs effectively.
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Acknowledgments
This paper is supported by the Project of National Natural Science Foundation of China under Grant No. 61271368 and Beijing Natural Science Foundation under Grant No. KZ201410009012.
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Wang, Y., Zhang, D. & Qi, Q. Liveness detection for dorsal hand vein recognition. Pers Ubiquit Comput 20, 447–455 (2016). https://doi.org/10.1007/s00779-016-0922-z
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DOI: https://doi.org/10.1007/s00779-016-0922-z