Thème :
Multimodal Biometrics
Présentation :
Multimodal biometrics refers to the use of multiple biometric traits or signals within a single recognition system in order to improve accuracy, reliability, and security. By fusing information from different modalities,such as facial images, fingerprints, voice signals, or physiological and behavioral data—multimodal biometric systems overcome the limitations of unimodal approaches. This research explores signal processing and machine learning techniques for feature extraction, data fusion, and decision-making, with applications in secure authentication, identity verification, and anti-spoofing systems.