Name
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%. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/CEC.2011.5949870 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
fusion,eigenface,score level fusion,evenly fused biometric modalities,local binary pattern,genetic and evolutionary computation,biometrics (access control),gec based multibiometric fusion,authorisation,genetic algorithms,steady-state genetic algorithms,sensor fusion,security of data,multi-biometrics,biometrics,face,genetics,feature extraction,pixel,accuracy,face recognition,evolutionary computing | Computer vision,Facial recognition system,Eigenface,Pattern recognition,Computer science,Local binary patterns,Evolutionary computation,Sensor fusion,Feature extraction,Artificial intelligence,Biometrics,Genetic algorithm | Conference |
ISSN | ISBN | Citations |
Pending | 978-1-4244-7834-7 | 7 |
PageRank | References | Authors |
0.51 | 6 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aniesha Alford | 1 | 32 | 5.91 |
| Caresse Hansen | 2 | 10 | 0.91 |
| Gerry V. Dozier | 3 | 326 | 44.63 |
| Kelvin S. Bryant | 4 | 25 | 6.01 |
| John C. Kelly | 5 | 76 | 15.77 |
| Tamirat Abegaz | 6 | 29 | 5.00 |
| Karl Ricanek | 7 | 165 | 18.65 |
| Damon L. Woodard | 8 | 522 | 31.66 |