Abstract

Fingerprint verification is used for person authentication. This has wide application from low risk to safety critical authentication systems. Research in this field has a long history. A number of approaches have been implemented for effective and efficient fingerprint verification. This article reports the results of quantitative comparison of different fingerprint verification approaches. We conducted an experiment of fingerprint verification using three approaches- biometric technique, Genetic algorithm and Back propagation neural network. The performance of the three approaches was assessed in terms of False Acceptance Rate (FAR), False Rejection Rate (FRR) and execution time. Our comparative analysis reveals that for small number of images there is no significant difference in performance among the chosen approaches.

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