Multimodal biometric authentication using speech and hand geometry fusion

Abstract

The paper presents biometric security system based on fusion of voice print and hand geometry recognition technologies. Speaker recognition works as text independent and is designed to verify a person using a short utterance. GMM method is used for speaker modeling and GMM-UBM classifier is used for process of matching. Hand geometry technology uses 21 extracted features from image of userpsilas hand and Euclidian distance for recognition. Information fusion in the multimodal system is performed at the matching score level, where scores obtained from matchers are combined using different normalization techniques and fusion rules. Multimodal system after fusion achieved 82.78% reduction in equal error rate over the better of the two independent systems.