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Complexity-Based Biometric Signature Verification

机译:基于复杂性的生物识别签名验证

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On-line signature verification systems are mainly based on two approaches: feature- or time functions-based systems (a.k.a. global and local systems). However, new sources of information can be also considered in order to complement these traditional approaches, reduce the intra-class variability and achieve more robust signature verification systems against forgers. In this paper we focus on the use of the concept of complexity in on-line signature verification systems. The main contributions of the present work are: 1) classification of users according to the complexity level of their signatures using features extracted from the Sigma LogNormal writing generation model, and 2) a new architecture for signature verification exploiting signature complexity that results in highly improved performance. Our proposed approach is tested considering the BiosecurID on-line signature database with a total of 400 users. Results of 5.8% FRR for a FAR = 5.0% have been achieved against skilled forgeries outperforming recent related works. In addition, an analysis of the optimal time functions for each complexity level is performed providing practical insights for the application of signature verification in real scenarios.
机译:在线签名验证系统,主要是基于两种方法:基于特征 - 功能或时间系统(又称为全球和本地系统)。然而,新的信息来源也可以为了对抗伪造补充这些传统的方法,减少类内变化,实现更强大的签名验证系统考虑。在本文中,我们专注于在网上签名验证系统中使用复杂的概念。本工作的主要贡献是:1)根据使用来自该Σ对数正态写入生成模型提取的特征是它们的签名的复杂性级别的用户的分类,和2),用于签名验证的新架构利用签名复杂的结果在高度改善表现。我们提出的方法进行测试考虑共400个用户的BiosecurID上线签名数据库。 5.8 %FRR的结果为一个FAR = 5.0 %已被本领域技术人员针对伪造优于最近相关工作来实现的。此外,在最佳时间功能,用于每个复杂层面的分析进行提供签名验证的实际的应用场景实际的见解。

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