大规模访问控制的生物识别技术——传统问题和创新方法

L. Riccardi, B. Peticone, M. Savastano
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引用次数: 3

摘要

由于复杂的国际形势,安全措施的增加正在迫使几种配备生物识别标识的门禁系统的实现。除技术问题外,一些与用户接受程度密切相关的非技术问题可能对应用程序的设计产生重大影响,并在选择要采用的生物识别技术时提出特定的选择。从面部识别是最广泛“接受”的生物识别技术之一的假设出发,并且由于在操作条件下显示的矛盾性能,这种方法很少被考虑用于高安全性应用,作者研究了通过原始方法改善误差数字的可能性。创新之处在于用从用户行为特征中提取的附加信息来“丰富”通过规范面部识别算法获得的模板。这项研究仍处于早期阶段,是在意大利国家研究委员会(CNR)和意大利国防部(MoD)合作的框架内进行的,研究领域是军事大院物理通道的强认证。本文的目的只是强调这种方法的潜力,因为第一个实验数据还不成熟,无法生成综合误差数据,如FAR和FRR。无论如何,区分同卵双胞胎的良好能力,这是面部识别中一个众所周知的问题,是继续研究的一个有希望的开端。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biometrics for massive access control - traditional problems and innovative approaches
The increase in security measures due to the complex international situation is forcing the realization of several access control systems equipped with biometric identifiers. Apart from technical problems, a number of nontechnical issues, strongly related to the user's acceptance, may have a strong influence on the design of the application and suggest particular choices in the selection of the biometric technique to be adopted. Starting from the assumption that facial recognition represents one of the most widely "accepted" biometric techniques, and that, due to contradictory performances shown in operating conditions, this methodology is seldom considered for high-security applications, the authors have investigated the possibility of improving the error figures by means of an original approach. The innovation consists in "enriching" the template obtained by means of canonical facial recognition algorithms with additional information extracted from behavioral characteristics of the user. The study, still in the early stage, is carried out in the framework of a collaboration between the National Research Council of Italy (CNR) and the Italian Ministry of the Defense (MoD) in the area of the strong authentication for physical access to military compounds. The aim of the present paper is only the highlighting of the potentiality of such an approach since first experimental data are not mature to generate consolidated error figures such as FAR and FRR. In any event, a very good capability in distinguishing between identical twins, a very well known problem in facial recognition, is a promising preamble for the continuation of the research.
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