Title :
GEC-based multi-biometric fusion
Author :
Alford, Aniesha ; Hansen, Caresse ; Dozier, Gerry ; Bryant, Kelvin ; Kelly, John ; Abegaz, Tamirat ; Ricanek, Karl ; Woodard, Damon L.
Author_Institution :
Center for Adv. Studies in Identity Sci., North Carolina A & T State Univ., Greensboro, NC, USA
Abstract :
In this paper, we use Genetic and Evolutionary Computation (GEC) to optimize the weights assigned to the biometric modalities of a multi-biometric system for score-level fusion. Our results show that GEC-based multi-biometric fusion provides a significant improvement in the recognition accuracy over evenly fused biometric modalities, increasing the accuracy from 90.77% to 95.24%.
Keywords :
authorisation; biometrics (access control); genetic algorithms; security of data; sensor fusion; GEC based multibiometric fusion; evenly fused biometric modalities; genetic and evolutionary computation; score level fusion; Accuracy; Biometrics; Face; Face recognition; Feature extraction; Pixel; Probes; Eigenface; Fusion; Local Binary Pattern; Multi-Biometrics; Steady-State Genetic Algorithms;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949870
