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Database of iris printouts and its application: Development of liveness detection method for iris recognition

机译:虹膜打印输出数据库及其应用:虹膜识别的活度检测方法的发展

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Liveness detection (often referred to as presentation attack detection) is the ability to detect artificial objects presented to a biometric device with an intention to subvert the recognition system. This paper presents the database of iris printout images with a controlled quality, and its fundamental application, namely development of liveness detection method for iris recognition. The database gathers images of only those printouts that were accepted by an example commercial camera, i.e. the iris template calculated for an artefact was matched to the corresponding iris reference of the living eye. This means that the quality of the employed imitations is not accidental and precisely controlled. The database consists of 729 printout images for 243 different eyes, and 1274 images of the authentic eyes, corresponding to imitations. It may thus serve as a good benchmark for at least two challenges: a) assessment of the liveness detection algorithms, and b) assessment of the eagerness of matching real and fake samples by iris recognition methods. To our best knowledge, the iris printout database of such properties is the first worldwide published as of today. In its second part, the paper presents an example application of this database, i.e. the development of liveness detection method based on iris image frequency analysis. We discuss how to select frequency windows and regions of interest to make the method sensitive to “alien frequencies” resulting from the printing process. The proposed method shows a very promising results, since it may be configured to achieve no false alarms when the rate of accepting the iris printouts is approximately 5% (i.e. 95% of presentation attack trials are correctly identified). This favorable compares to the results of commercial equipment used in the database development, as this device accepted all the printouts used. The method employs the same image as used in iris recognition process, hence no investments into- the capture devices is required, and may be applied also to other carriers for printed iris patterns, e.g. contact lens.
机译:活跃度检测(通常称为呈现攻击检测)是一种检测呈现给生物识别设备的人造物体的能力,目的是破坏识别系统。本文提出了一种具有可控质量的虹膜打印输出图像数据库,并介绍了其基础应用,即虹膜识别的活度检测方法的发展。该数据库仅收集示例商用相机接受的那些打印输出的图像,即,为伪像计算的虹膜模板与活眼的相应虹膜参考相匹配。这意味着所采用的模仿品的质量不是偶然的,而是受到精确控制的。该数据库由243张不同眼睛的729张打印输出图像和1274张真实眼睛的图像(对应于仿制图像)组成。因此,它可以作为至少两个挑战的良好基准:a)活度检测算法的评估,以及b)通过虹膜识别方法评估匹配真实样本和伪样本的渴望。据我们所知,此类属性的虹膜打印输出数据库是迄今为止在全球范围内第一个发布的数据库。在第二部分中,本文介绍了该数据库的示例应用程序,即基于虹膜图像频率分析的活力检测方法的开发。我们讨论如何选择频率窗口和感兴趣的区域,以使该方法对打印过程中产生的“异频”敏感。所提出的方法显示出非常有希望的结果,因为它可以配置为在接受虹膜打印输出的比率大约为5%(即正确识别了95%的演示攻击试验)时不会出现错误警报。与数据库开发中使用的商用设备的结果相比,这是有利的,因为该设备可以接受所有使用的打印输出。该方法采用与虹膜识别过程中所使用的图像相同的图像,因此不需要对捕获装置进行投资,并且该方法还可以应用于印刷虹膜图案的其他载体。隐形眼镜。

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