Fingerprint vitality detection, quality evaluation and forensics: bibliography
Fingerprint Liveness detection is the problem of assessing if a fingerprint image, acquired by an electronic scanner, comes from a "live" finger or an artificial replica. Recent works have shown that it is possible not only to replicate a fingerprint, but also to deceive an electronic scanner and circumvent a fingerprint verification systems (Matsumoto et al., 2002; Sandstrom, 2004).
In order to face with this issue, several approaches to fingerprint liveness detection have been proposed. Some of them are based on the addition of specific hardware able to detect, for example, the heartbeat of the finger. But these methods increase the cost and make these systems strongly invasive. Therefore, several algorithms aimed to detect the "fingerprint liveness" from the analysis of related images have been proposed. The problem is to extract several "liveness" features and perform a classification of the fingerprint image according to "live" and "fake" classes.
Approaches at the state-of-the-art exploits characteristics as perspiration (Derakshani, 2003; Parthasaradhi, 2005), the elastic deformation (Antonelli et al., 2006; Chen and Jain, 2005) and the analysis of images based on wavelet transform (Moon et al., 2005; Tan and Schuckers, 2006).
The problem also involves the quality of fingerprint images, since this feature impacts on the performance of verification system strongly. This problem is different if fingerprint images are considered in the context of standard personal authentication systems, or forensic applications. In the first case, it has been studied the impact of quality of artificial fingerprint replicas (Fronthaler et al., 2008). In the second case, the problem involves the ability of police officers of clearly enhance the fragment of fingerprint released in the crime scene, according to the most recent approaches (Berger et al. 2006).
(Antonelli et al., 2006) A. Antonelli, R. Cappelli, D. Maio, D. Maltoni, Fake Finger Detection by Skin Distortion Analysis, IEEE Transactions on Information Forensics and Security, Vol.1, no.3, 360-373, 2006.
(Berger et al., 2006) C.E.H Berger, J.A. de Koeijer, W. Glas, and T.H. Madhuizen, Color separation in forensic image processing, Journal of Forensic Sciences, 51 (1) 100-102, 2006.
(Chen and Jain, 2005) Y. Chen, A.K. Jain, S. Dass, Fingerprint deformation for spoof detection, Biometric Symposium, Cristal City, VA, 2005.
(Derakshani et al, 2003) R. Derakhshani, S. Schuckers, L. Hornak, L. O'Gorman, Determination of vitality from a non-invasive biomedical measurement for use in fingerprint scanners, Pattern Recognition 36 (2)383-396, 2003.
(Fronthaler et al., 2008) H. Fronthaler, K. Kollreider, J. Bigun, J. Fierrez, F. Alonso-Fernandez, J. Ortega-Garcia and J. Gonzalez-Rodriguez, Fingerprint Image Quality Estimation and its Application to Multi-Algorithm Verification, IEEE Trans. on Information Forensics and Security, Vol. 3, n. 2, pp. 331-338, June 2008.
(Matsumoto et al., 2002) T. Matsumoto, H. Matsumoto, K. Yamada e S.Hoshino. Impact of artificial "gummy" fingers on fingerprint systems. In Proceedings of SPIE Vol. 4677, Optical Security and Counterfeit Deterence Techniques IV, Yokohama, Japan, Gennaio 2002.
(Moon et al., 2005) Y.S. Moon, J.S., Chen, K.C. Chan, K. So, K.C. Woo1, Wavelet based fingerprint liveness detection, Electronics Letters, 41 (20),1112-1113, 2005.
(Parthasadadhi et al., 2005) S. Parthasaradhi, R. Derakhshani, L. Hornak, S. Schuckers, Time-series detection of perspiration as a vitality test in fingerprint devices, IEEE Trans. On Systems, Man and Cybernetics, Part C, 35 (3),335-343,2005.
(Sandstrom, 2004) M. Sandstrom, "Liveness detection in fingerprint recognition systems", Linkoping, June 2004
(Tan and Schuckers, 2006) B. Tan, S. Schuckers, Liveness detection for fingerprint scanners based on the statistics of wavelet signal processing, Conference on Computer Vision Pattern Recognition Workshop (CVPRW06), 2006.