Multimodal Biometrics for user authentication

The main aim of this paper is to provide multilevel authentication in biometric systems. Multimodal biometric is the usage of multiple biometric indicators by personal identification systems for identifying the individuals. Multimodal authentication provides more level of authentication than unimodal biometrics which uses only one biometric data such as fingerprint or face or palm print or iris. In this paper, we are using fingerprint and iris of a person for the automatic identification of an individual by combining finger print and iris of a person at the matching-score level. A technique called Minutiae matching and Edge detection is used for this purpose. The performance of the proposed technique has been evaluated and accuracy has been increased by minimizing the FAR (False Acceptance Rate) and FRR (False Rejection Rate).