A wavelet-based approach to detecting liveness in fingerprint scanners
Aditya Abhyankar, Stephanie Schuckers · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
In this work, a method to provide fingerprint vitality authentication, in order to improve vulnerability of fingerprint identification systems to spoofing is introduced. The method aims at detecting 'liveness' in fingerprint scanners by using the physiological phenomenon of perspiration. A wavelet based approach is used which concentrates on the changing coefficients using the zoom-in property of the wavelets. Multiresolution analysis and wavelet packet analysis are used to extract information from low frequency and high frequency content of the images respectively. Daubechies wavelet is designed and implemented to perform the wavelet analysis. A threshold is applied to the first difference of the information in all the sub-bands. The energy content of the changing coefficients is used as a quantified measure to perform the desired classification, as they reflect a perspiration pattern. A data set of approximately 30 live, 30 spoof, and 14 cadaver fingerprint images was divided with first half as a training data while the other half as the testing data. The proposed algorithm was applied to the training data set and was able to completely classify 'live' fingers from 'not live' fingers, thus providing a method for enhanced security and improved spoof protection.