Fast and Accurate Fingerprint Verification

Speed and accuracy are the prerequisites of a biometric authentication system. However, most fingerprint verification methods compromise speed for accuracy or vice versa. In this paper we propose a novel fingerprint verification algorithm as a solution to this problem. The algorithm is inspired by a basic Computer Vision approach to model-based recognition of objects-alignment. We pose the problem of fingerprint matching as one of matching the corresponding feature sets. We propose a novel transformation consistency checking scheme to make verification accurate. We employ an early elimination strategy to eliminate inconsistent transformations and thereby achieve significant speed-up. Further speed-up is obtained by sampling based on geometric nearness. Our algorithm is simple, intuitive, easy to implement even on the simplest hardware and does not make any assumption on the availability of singularities like core and delta in the fingerprint. We report our results on three representative fingerprint databases.