Feature Level Fusion of Face and Palmprint Biometrics

被引：0
|
作者：
Kisku, Dakshina Ranjan [1 ]
Gupta, Phalguni [2 ]
Sing, Jamuna Kanta [3 ]
机构：
[1] Dr BC Roy Engn Coll, Dept Comp Sci & Engn, Durgapur 713206, India
[2] Indian Inst Technol, Dept Comp Sci & Engn, Kanpur 208016, Uttar Pradesh, India
[3] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, W Bengal, India
来源：
STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION | 2010年 / 6218卷
关键词：
Biometrics; Feature Level Fusion; Face; Palmprint; Isomorphic Graph; K-Medoids Partitioning Algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a feature level fusion of face and palmprint biometrics. It uses the improved K-medoids clustering algorithm and isomorphic graph. The performance of the system has been verified by two distance metrics namely, K-NN and normalized correlation metrics. It uses two multibiometrics databases of face and palmprint images for testing. The experimental results reveal that the feature level fusion with the improved K-medoids partitioning algorithm exhibits robust performance and increases its performance with utmost level of accuracy.
引用
收藏
页码：512 / +
页数：3
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