A Multimodal Biometric User Verification System with Identical Twin using SVM 2

Abstract

A biometric system recognizes unique features of a distinct found on the resolution and examining the behavioral and physical characteristics. Yet, the objective of existing search is to identify and verify the authorized person but it is inefficient due to noisy data, unacceptable false rates and identical twins. However, the identical twin has a high complexity owing to the closest genetic relationship with overall biometric recognition. Multimodal biometric system uses multiple sensors to conquer the detriment of single biometric system. Hence, this method uses Adoptive Median Filter for reducing image distortion and SVM2 classification to improve the false rate which ensure reliable and precise biometric recognition system. This propounds a multimodal biometric user verification system by integrating fingerprint; facial recognition and lip print images which produce a robust, reliable and accurate authentication result.