New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System

Abstract

This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification.

Optimization Techniques for Human Multi-Biometric Recognition System

“…The average true-positive rate and accuracy of the suggested fusion system were 99.8 and 99.6 percent, respectively. Mohammed et al [15], delved deeply into the individual identification potential of multi-biometric fusion. The Dis-Eigen algorithm is a novel feature-level algorithm.…”