LPCC and SIFT Based Biometric Amalgamation of Iris and Speech for Authentication and Identification
Multimodal biometric system verifies a person's identity based on physiological (face, iris and fingerprint) or behavioral biometric traits (voice and signature). During this paper, a brand new multimodal biometric system is developed i.e. using iris and speech. Initially, Iris and Speech recognition systems area unit developed singly by extracting their features from the Independent Component Analysis (ICA) technique for iris and from Gamma tone Frequency Cepstral Coefficients (GFCCs) technique for speech. In proposed work, the speech and iris traits area unit combined along and also its performance is verified throughout authentication with the help of techniques Scale Invariant Feature Transform (SIFT) and Linear Predictive Cepstral Coefficient (LPCC).