A Bayesian approach for modeling sensor influence on quality, liveness and match score values in fingerprint verification

Recently a number of studies in fingerprint verification have combined match scores with quality and liveness measures in order to thwart spoof attacks. However, these approaches do not explicitly account for the influence of the sensor on these variables. In this work, we propose a graphical model that accounts for the impact of the sensor on match scores, quality and liveness measures. The proposed graphical model is implemented using a Gaussian Mixture Model based Bayesian classifier. Effectiveness of the proposed model has been assessed on the LivDet11 fingerprint database using Biometrika and Italdata sensors.

[1]  Suneeta Agarwal,et al.  Local binary pattern and wavelet-based spoof fingerprint detection , 2008, Int. J. Biom..

[2]  Arun Ross,et al.  Biometric Sensor Interoperability: A Case Study in Fingerprints , 2004, ECCV Workshop BioAW.

[3]  Anil K. Jain,et al.  Unsupervised Learning of Finite Mixture Models , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Norman Poh,et al.  Biometric system design under zero and non-zero effort attacks , 2013, 2013 International Conference on Biometrics (ICB).

[5]  Lakhmi C. Jain,et al.  Introduction to Bayesian Networks , 2008 .

[6]  Arun Ross,et al.  Handbook of Multibiometrics , 2006, The Kluwer international series on biometrics.

[7]  Arun Ross,et al.  Analysis of user-specific score characteristics for spoof biometric attacks , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

[8]  Arun Ross,et al.  Combining match scores with liveness values in a fingerprint verification system , 2012, 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[9]  Stephanie Schuckers,et al.  Fingerprint Liveness Detection Using Local Ridge Frequencies and Multiresolution Texture Analysis Techniques , 2006, 2006 International Conference on Image Processing.

[10]  Josef Kittler,et al.  Quality-Based Score Normalization With Device Qualitative Information for Multimodal Biometric Fusion , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

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

[12]  Sébastien Marcel,et al.  Anti-spoofing in Action: Joint Operation with a Verification System , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops.