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

页码：2071 / 2074

页数：4

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