Human Detection Multi-Modal Biometric System

This paper proposes the multimodal biometrics system for identity verification of human being in a very efficient manner by using various traits such as, face, fingerprint, iris, voice and signature. Biometrics based personal identification is regarded as an effective method for automatically recognizing, with a high confidence a person’s identity. The proposed system is designed for applications where the training database contains face, fingerprint, iris, voice and signature for each individual. The final decision is made by fusion of all the biometric traits, on “matching score level architecture” in which feature vectors are created independently for query images and are then compared to the enrollment templates which are stored during database preparation for each biometric trait. Based on the proximity of feature vector and template, each subsystem computes its own matching score. These individual scores are finally combined into a total score, which is passed to the decision module i.e. it should be large enough to pass the threshold value. Multimodal system is developed through fusion of face, fingerprint, iris, and voice and signature recognition.