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Benchmarking desktop and mobile handwriting across COTS devices: The e-BioSign biometric database

机译:跨COTS设备对台式机和移动手写进行基准测试:e-BioSign生物识别数据库

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摘要

This paper describes the design, acquisition process and baseline evaluation of the new e-BioSign database, which includes dynamic signature and handwriting information. Data is acquired from 5 different COTS devices: three Wacom devices (STU-500, STU-530 and DTU-1031) specifically designed to capture dynamic signatures and handwriting, and two general purpose tablets (Samsung Galaxy Note 10.1 and Samsung ATIV 7). For the two Samsung tablets, data is collected using both pen stylus and also the finger in order to study the performance of signature verification in a mobile scenario. Data was collected in two sessions for 65 subjects, and includes dynamic information of the signature, the full name and alpha numeric sequences. Skilled forgeries were also performed for signatures and full names. We also report a benchmark evaluation based on e-BioSign for person verification under three different real scenarios: 1) intra-device, 2) inter-device, and 3) mixed writing-tool. We have experimented the proposed benchmark using the main existing approaches for signature verification: feature- and time functions-based. As a result, new insights into the problem of signature biometrics in sensor-interoperable scenarios have been obtained, namely: the importance of specific methods for dealing with device interoperability, and the necessity of a deeper analysis on signatures acquired using the finger as the writing tool. This e-BioSign public database allows the research community to: 1) further analyse and develop signature verification systems in realistic scenarios, and 2) investigate towards a better understanding of the nature of the human handwriting when captured using electronic COTS devices in realistic conditions.
机译:本文介绍了新的e-BioSign数据库的设计,获取过程和基线评估,其中包括动态签名和手写信息。数据是从5种不同的COTS设备中获取的:三个专门用于捕获动态签名和手写的Wacom设备(STU-500,STU-530和DTU-1031),以及两个通用平板电脑(三星Galaxy Note 10.1和三星ATIV 7)。对于这两种三星平板电脑,使用手写笔和手指来收集数据,以便研究在移动场景中签名验证的性能。在两个阶段中针对65个主题收集了数据,其中包括签名的动态信息,全名和字母数字序列。还对签名和全名进行了熟练的伪造。我们还报告了基于e-BioSign的基准评估,用于在以下三种不同的真实情况下进行人员验证:1)设备内,2)设备间和3)混合书写工具。我们已经使用现有的主要签名验证方法对建议的基准进行了实验:基于特征和时间函数。结果,获得了对传感器可互操作场景中的签名生物识别技术问题的新见解,即:处理设备互操作性的特定方法的重要性,以及对使用手指作为笔迹获得的签名进行更深入分析的必要性工具。该e-BioSign公共数据库使研究团体能够:1)在现实情况下进一步分析和开发签名验证系统,以及2)进行调查,以更好地理解在现实情况下使用电子COTS设备捕获人类手写的本质。

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