Multimodel Biometric Authentication System For Accurate Identity Verification

Biometrics refers to the automatic identification of an individual based on his/her physiological or behavioral traits. Unimodal biometric authentication systems perform person recognition based on a single source of biometric information and are affected by problems like noisy sensor data, non-universality and lack of individuality of the chosen biometric trait. Some of the limitations imposed by unimodal biometric systems (that is, biometric systerns that rely on the evidence of a single biometric trait) can be overcome by using multiple biometric modalities. Such systems, known as Multimodal biometric systems, are expected to be more reliable due to the presence of multiple, fairly independent pieces of evidence. A multimodal biometric authentication system integrates information from multiple biometric sources to compensate for the limitations in per-formance of each individual biometric system. This paper proposes the multimodal biometric authentication system for identity verification using four traits i.e., face, fingerprint, iris and signature. The proposed system is designed for applications where the training database contains a face, iris, fingerprint and/or signature for each individual. The final decision is made by fusion at "matching score level