Secure Multimodal Biometric Recognition Based on Speech, Face and Fingerprint Using Feature Level Fusion Approach

Abstract

Biometric is the field for user authentication and verification as well as for providing security from unauthorized access. Various biometric traits have been utilized for development of secure model to provide security. Uni-modal biometric system has been designed to authorize user identity. These systems use single biometric traits that can be used for recognition process. Biometric traits are face, finger, iris, palm, vain and speech. On the basis of these systems authentication models have been prepared that can be used for user validation. The main problem in uni-modal biometric system is that due to use of single trait of biometric it is an easy process to capture biometric identification of individual. In recent research multimodal biometric authentication systems have been developed that can be used for authentication of the users. To overcome security threats in the proposed work face finger and voice based traits have been included to develop more accurate and secure system.