A novel fingerprint pressure deformation algorithm for biometric authentication

Biometrics is the automated use of physiological or behavioural characteristics to determine or verify identity. Each biometric method has its strengths and weaknesses. Biometrics brings a new dimension to individual identity verification. It allows the process to be automated and unsupervised where applicable whilst providing levels of accuracy and consistency that simply cannot be guaranteed by traditional methods relying solely on human interpretation. However, biometric verification is not infallible and its implementation requires an understanding of both the technology and the human interface. Careful consideration must be given to all aspects of biometric system design including the user interface, the technical architecture and the environment in which it is to be deployed The skin-dependant biometric method (finger-scan, and hand-scan) have their weakness on the factor of skin elasticity and deformation. This paper presents a new algorithm that captures the effects of pressure on skin and the accuracy of finger matching. The model accounts for the various levels of dynamic non-linearity that exist during the capture of the data for fingerprints. Furthermore, a computationally efficient matching algorithm has been used to accurately match fingerprints. Benchmark tests of 300 images have been used to challenge the algorithm The tests, in addition, have included added noise and different orientatiosn. The novel algorithm under these difficult tests has been shown to be robust and on average accuracy is over 90 percent.