Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Fingerprint Recognition
Handbook of Fingerprint Recognition
Liveness Detection for Fingerprint Scanners Based on the Statistics of Wavelet Signal Processing
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Handbook of Biometrics
Vitality Detection from Fingerprint Images: A Critical Survey
ICB '07 Proceedings of the international conference on Advances in Biometrics
Fingerprint Liveness Detection Using Curvelet Energy and Co-Occurrence Signatures
CGIV '08 Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation
Texture and Wavelet-Based Spoof Fingerprint Detection for Fingerprint Biometric Systems
ICETET '08 Proceedings of the 2008 First International Conference on Emerging Trends in Engineering and Technology
First International Fingerprint Liveness Detection Competition--LivDet 2009
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Analysis of Fingerprint Pores for Vitality Detection
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Multi-scale local binary pattern with filters for spoof fingerprint detection
Information Sciences: an International Journal
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Fingerprint liveness detection is aimed to detect if a fingerprint image, sensed by an electronic device, belongs to an "alive" fingertip or to be an artificial replica of it. Recent studies have shown that a fingerprint can be replicated and, if a clever attacker tries to evade the system, this is an issue. Accordingly, several countermeasures in terms of "fingerprint liveness" detection algorithms have been proposed, but never compared on a benchmark data set, internationally accepted by the research community. In this paper, we present some recent experimental results on several state-of-the-art fingerprint liveness detection algorithms on the datasets available at Second International Fingerprint Liveness Detection Competition (LivDet 2011). The results we proposed help assessing which are the more effective approaches used so far.