Multimodal biometrics system for efficient human recognition

Abstract

This paper proposes the multimodal biometrics system for identity verification using four traits i.e., face, fingerprint, iris and signature. The proposed system is designed for applications where the training database contains a face, iris, two fingerprint images and/or one or two signature image(s) for each individual. The final decision is made by fusion at "matching score level architecture" in which feature vectors are created independently for query images and are then compared to the enrollment templates which are stored during database preparation for each biometric trait. Based on the proximity of feature vector and template, each subsystem computes its own matching score. These individual scores are finally combined into a total score, which is passed to the decision module. Multimodal system is developed through fusion of face, fingerprint, iris and signature recognition. This system is tested on IITK database and the overall accuracy of the system is found to be more than 97% accurate with FAR and FRR of 2.46% and 1.23% respectively.

An Efficient Fusion Strategy for Multimodal Biometric System

“…One way to overcome these problems is the use of multi-biometrics. This approach also enables a user who does not possess a particular biometric identifier to still enroll and authenticate using other traits, thus eliminating the enrollment problems and making it universal (Gupta et al, 2006).…”

BIOMET: A Multimodal Biometric Authentication System for Person Identification and Verification using Fingerprint and Face Recognition

“…So, the final score , denoted as MSFinal is given by MS Final = (a×MS Face +b×MS Finger ) /2 [7] where MS Face = matching score of face MS Finger = matching score of fingerprint and a, b, are the weights assigned to the various traits.…”