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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Personal identity verification by serial fusion of fingerprint and face matchers
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Personal identity verification by serial fusion of fingerprint and face matchers

机译:通过指纹和面部匹配器的序列融合来验证个人身份

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摘要

The use of personal identity verification systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variations and fraudulent attacks. Usually multi-modal fusion of biometrics is performed in parallel at the score-level by combining the individual matching scores. This parallel strategy exhibits some drawbacks: (i) all available biometrics are necessary to perform fusion, thus the verification time depends on the slowest system: (ii) some users could be easily recognizable using a certain biometric instead of another one and (iii) the system invasiveness increases. A system characterized by the serial combination of multiple biometrics call be a good trade-off between verification time, performance and acceptability. However, these systems have been poorly investigated, and no support for designing the processing chain has been given so far. In this paper, we propose a novel serial scheme and a simple mathematical model able to predict the performance of two serially combined matchers as function of the selected processing Chain. Our model helps the designer in finding the processing chain allowing a trade-off, in particular, between performance and matching time. Experiments carried out on well-known benchmark data sets made up of face and fingerprint images support the usefulness of the proposed methodology and compare it with standard parallel fusion.
机译:已提出将个人身份验证系统与多模式生物特征识别结合使用,以提高针对环境变化和欺诈性攻击的性能和鲁棒性。通常,生物特征的多模式融合是通过组合各个匹配得分在得分级别上并行执行的。这种并行策略存在一些缺陷:(i)执行融合需要所有可用的生物特征识别,因此验证时间取决于最慢的系统:(ii)使用某个生物特征识别而不是另一个生物识别可以轻松识别某些用户,并且(iii)系统的入侵性增加。一个以多个生物特征识别序列组合为特征的系统,是在验证时间,性能和可接受性之间的良好折衷。但是,对这些系统的研究很少,到目前为止,尚未提供对设计处理链的支持。在本文中,我们提出了一种新颖的串行方案和一个简单的数学模型,该方案可以预测两个串行组合的匹配器作为所选处理链的函数的性能。我们的模型可帮助设计师找到允许在性能和匹配时间之间进行权衡的处理链。在由面部和指纹图像组成的知名基准数据集上进行的实验支持了所提出方法的有用性,并将其与标准并行融合进行了比较。

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