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LivDet iris 2017 — Iris liveness detection competition 2017

机译:LivDet Iris 2017 —虹膜活动检测比赛2017

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Presentation attacks such as using a contact lens with a printed pattern or printouts of an iris can be utilized to bypass a biometric security system. The first international iris liveness competition was launched in 2013 in order to assess the performance of presentation attack detection (PAD) algorithms, with a second competition in 2015. This paper presents results of the third competition, LivDet-Iris 2017. Three software-based approaches to Presentation Attack Detection were submitted. Four datasets of live and spoof images were tested with an additional cross-sensor test. New datasets and novel situations of data have resulted in this competition being of a higher difficulty than previous competitions. Anonymous received the best results with a rate of rejected live samples of 3.36% and rate of accepted spoof samples of 14.71%. The results show that even with advances, printed iris attacks as well as patterned contacts lenses are still difficult for software-based systems to detect. Printed iris images were easier to be differentiated from live images in comparison to patterned contact lenses as was also seen in previous competitions.
机译:诸如利用具有印刷图案或虹膜打印输出的隐形眼镜之类的演示攻击可用于绕过生物安全系统。为了评估表示攻击检测(PAD)算法的性能,于2013年启动了首届国际虹膜活动竞赛,2015年则举办了第二届竞赛。本文介绍了第三次竞赛,即LivDet-Iris 2017的结果。基于软件的三种提出了演示攻击检测方法。实时图像和欺骗图像的四个数据集通过附加的交叉传感器测试进行了测试。新的数据集和新颖的数据情况导致该竞赛比以前的竞赛具有更高的难度。匿名者获得了最佳结果,拒绝的实时样本率为3.36%,接受的欺骗样本率为14.71%。结果表明,即使取得了进步,基于软件的系统仍难以检测到印刷的虹膜攻击以及带图案的隐形眼镜。与以前的比赛中所看到的相比,印刷的虹膜图像与带图案的隐形眼镜相比,更容易与实时图像区分开。

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