CNN-BASED MULTIMODAL BIOMETRIC SYSTEM

Abstract

Unimodal biometrics is less accurate and safe because to a number of issues,
including noisy data, intraclass variance, interclass similarities, non-universality, and spoofing.
Multimodal biometrics is employed to get around these issues and boost security. For personal
authentication, multimodal biometrics uses data from several sources. As multimodal biometrics
are on the cutting edge of unimodal biometrics, they are becoming increasingly popular these
days. An introduction to multimodal biometrics is provided in this publication. The general
multimodal biometrics block diagram, the multimodal biometric system's modules, the various
fusion levels in multimodal biometrics, and related studies are all described in this study.