GEC-Based Multi-Biometric Fusion

被引：0
|
作者：
Alford, Aniesha [1 ]
Hansen, Caresse [1 ]
Dozier, Gerry [1 ]
Bryant, Kelvin [1 ]
Kelly, John [1 ]
Abegaz, Tamirat [1 ]
Ricanek, Karl [1 ]
机构：
[1] North Carolina A&T State Univ, Ctr Adv Studies Ident Sci, Greensboro, NC 27409 USA
来源：
2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年
基金：
美国国家科学基金会;
关键词：
Eigenface; Fusion; Local Binary Pattern; Multi-Biometrics; Steady-State Genetic Algorithms;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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%.
引用
收藏
页码：2071 / 2074
页数：4
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