Fingerprint and Voice Identification in Biometric Security Systems using Neural Network

Perhaps the most essential application of correct personal identification is securing limited access systems from spiteful attacks. Among all the presently employed biometric techniques, fingerprint and voice identification systems have received the most attention due to the long history of fingerprints and their extensive use in forensics and uniqueness of voice for better identification. This paper deals with the issue of selection of an optimal algorithm for fingerprint and voice matching in order to design a system that matches required specifications in performance and accuracy. Two competing algorithms were compared against a common database using MATLAB simulations.