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Combined features for an Secured Authentication system

Biometrics based personal identification is regarded as an effective method for automatically recognizing, with a high confidence, a person’s identity. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech signal and palmprint. The proposed system is designed for applications where the training data contains a speech signal and palmprint. It is well known that the performance of person authentication using only speech signal or palmprint is deteriorated by feature changes with time. Integrating the palmprint and speech information increases robustness of person authentication. The final decision is made by fusion at matching score level architecture in which feature vectors are created independently for query measures and are then compared to the enrolment templates, which are stored during database preparation. Multimodal system is developed through fusion of speech signal and palmprint recognition.