利用多模态技术实现生物识别认证的更高准确性

Firas Saad Rihan, Fadel Alabbas Khalil, M. Aoude
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引用次数: 0

摘要

生物特征认证是安全系统的一个重要方面,它基于独特的生物特征来识别个人。然而,单峰生物识别系统确实存在安全性和准确性问题。为了提高准确性,本文提出了一种结合指纹、声音、面部和虹膜数据的多模态生物识别认证方法。通过最小化错误接受率(FAR)和错误拒绝率(FRR),以及与现有技术相比具有更高的准确性,评估了所提出技术的性能。本文强调了多模态生物识别方法的价值,以及它们如何提高识别系统的精度和安全性。该技术对更加可靠和健壮的生物识别认证系统的发展产生了重大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Achieving Higher Accuracy in Biometric Authentication with Multimodal Techniques
Biometric authentication is an important aspect of security systems that identify individuals based on unique biological traits. Unimodal biometric systems do, however, have security and accuracy issues. In order to increase accuracy, this article suggests a multimodal biometric authentication method that combines fingerprint, voice, face, and iris data. By minimizing the false acceptance rate (FAR) and false rejection rate (FRR), as well as by its higher accuracy when compared to existing techniques, the performance of the proposed technique is assessed. The article emphasizes the value of multimodal approaches to biometric authentication as well as how they could improve the precision and security of identification systems. The development of more dependable and robust biometric authentication systems is significantly impacted by the proposed technique.
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