Liveness detection for dorsal hand vein recognition

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.

[1]  Satoshi Hoshino,et al.  Impact of artificial "gummy" fingers on fingerprint systems , 2002, IS&T/SPIE Electronic Imaging.

[2]  Carlo Sansone,et al.  Combining perspiration- and morphology-based static features for fingerprint liveness detection , 2012, Pattern Recognit. Lett..

[3]  Ilias Maglogiannis,et al.  Face detection and recognition of natural human emotion using Markov random fields , 2007, Personal and Ubiquitous Computing.

[4]  Chris Roberts,et al.  Biometric attack vectors and defences , 2007, Comput. Secur..

[5]  Ton van der Putte,et al.  Biometrical Fingerprint Recognition: Don't Get Your Fingers Burned , 2001, CARDIS.

[6]  Lin Sun,et al.  Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[7]  Niu Jin-xin Power Spectrum Estimation Based on AR Model , 2011 .

[8]  Yiding Wang,et al.  Hand-dorsa vein recognition based on partition Local Binary Pattern , 2010, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS.

[9]  Rui Chen,et al.  Liveness detection for iris recognition using multispectral images , 2012, Pattern Recognit. Lett..

[10]  Sébastien Marcel,et al.  Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition , 2014, IEEE Transactions on Image Processing.

[11]  Venu Govindaraju,et al.  Enhancing biometric recognition with spatio-temporal reasoning in smart environments , 2012, Personal and Ubiquitous Computing.

[12]  Yiding Wang,et al.  Liveness Detection of Dorsal Hand Vein Based on the Analysis of Fourier Spectral , 2013, CCBR.