A wavelet based invigoration check in fingerprint scanners

By virtue of using simple, inexpensive techniques it is possible to delude fingerprint scanners. An antidote against such fraudulent attacks is suggested in this paper. This work emphasizes on quantifying liveness for fingerprint scanners using wavelet energy analysis of fingerprint images. From the images captured at two time stamps the perspiration changes along the finger ridges are sensed and used as liveness measure. Multiresolution analysis and wavelet packet analysis is performed for low and high frequency data. Orthogonal Daubechies filters are designed to analyze the non-stationary information efficiently.Only those wavelet coefficient which experience an energy change of more than 40% are used for liveness after normalization. The proposed algorithm was applied to a data set of approximately 58 live, 50 spoof and 28 cadaver fingerprint images captured at 0 sec and 2 or 5 sec. The algorithm was tested for different underlying fingerprint sensing technologies including optical (secugen), optoelectrical (ethentica) and capacitive DC (precise biometrics). Classification results are presented for all the scanners and for both the time windows.