A STUDY OF MULTIMODAL BIOMETRIC SYSTEM

Abstract

Biometrics is the area of automatic persons identification based on the biological characteristics of human body. As in our day-to-day life automatic person’s identification is an important task as per the high security issues. Unimodal biometric system has many limitations about security, accuracy, performance and robustness. A multimodal biometric system combines information obtained from different biometric Examples of noisy data are voice changed by cold or a characteristics and offers better recognition performance as fingerprint with a scratch. Noisy data could also be the result compared to the unimodal system. Multimodal biometrics is the of faulty or incorrectly kept sensors for example gathering of level based approach where fusion takes place at different levels dirt on a fingerprint sensor or harsh ambient conditions for as sensor, feature, matching score and decision. Fusion at example in a face recognition system, no clear data due to matching score level is more preferable because matching ranks poor light on user’s face. Noisy biometric data may increase are easily available and contains sufficient information to false reject rate. distinguish. There is sufficient scope to design a proficient matching score level fusion approach. Fusion at matching score level is likely to provide better recognition performance as it contains more contented information which is both feasible and practical. So this is the review paper mainly focuses on the study of matching score level fusion in multimodal biometric system.