Fusion of electrocardiogram with unobtrusive biometrics: An efficient individual authentication system

被引:58
|
作者
Singh, Yogendra Narain [1 ]
Singh, Sanjay Kumar [2 ]
Gupta, Phalguni [3 ]
机构
[1] Gautam Buddh Tech Univ, Inst Engn & Technol, Dept Comp Sci & Engn, Lucknow, Uttar Pradesh, India
[2] Banaras Hindu Univ, Inst Technol, Dept Comp Engn, Varanasi 221005, Uttar Pradesh, India
[3] Indian Inst Technol Kanpur, Dept Comp Sci & Engn, Kanpur, Uttar Pradesh, India
关键词
Electrocardiogram (ECG); Multibiometrics; Biometrics fusion; Individual authentication; ECG;
D O I
10.1016/j.patrec.2012.03.010
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 explores the effectiveness of a novel multibiometric system that is resulted from the fusion of the electrocardiogram (ECG) with an unobtrusive biometric face and another biometric fingerprint which is known to be a least obtrusive for efficient individual authentication. The unimodal systems of the face and the fingerprint biometrics are neither secure nor they can achieve the optimum performance. Using the ECG signal as one of the biometrics offer advantage to a multibiometric system that ECG is inherited to an individual which is confidential, secured and difficult to be forged. It has an inherent feature of vitality signs that ensures a strong protection against spoof attacks to the system. Transformation based score fusion technique is used to measure the performance of the fused system. In particular, the weighted sum of score rule is used where weights are computed using equal error rate (EER) and match score distributions of the unimodal systems. The performance of the proposed multibiometric system is measured using EER and receiver operating characteristic (ROC) curve. The results show the optimum performance of the multibiometric system fusing the ECG signal with the face and fingerprint biometrics which is achieved to an EER of 0.22%, as compared to the unimodal systems that have the EER of 10.80%, 4.52% and 2.12%, respectively for the ECG signal, face and fingerprint biometrics. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:1932 / 1941
页数:10
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