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

机译:心电图与不干扰生物特征的融合:高效的个人身份验证系统

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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.
机译:本文探讨了一种新颖的多重生物测量系统的有效性,该系统是由心电图(ECG)与不显眼的生物特征识别脸和另一种对有效的个人身份验证而言最不显眼的生物识别指纹融合而成的。人脸和指纹生物特征识别的单峰系统既不安全,也无法实现最佳性能。将ECG信号用作生物特征之一为ECG继承给机密,安全且难以伪造的个人的多生物识别系统提供了优势。它具有生命迹象的固有功能,可确保对系统的欺骗攻击提供强大的保护。基于转换的分数融合技术用于衡量融合系统的性能。特别是,在使用等错误率(EER)和单峰系统的匹配得分分布计算权重的情况下,使用得分规则的加权和规则。使用EER和接收器工作特性(ROC)曲线来测量所提出的多生物系统的性能。结果表明,与具有10.80%,4.52%和2.12%EER的单峰系统相比,将ECG信号与面部和指纹生物特征融合在一起的多生物系统的最佳性能达到了0.22%的EER。分别用于ECG信号,面部和指纹生物识别。

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