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Iris presentation attack detection: Where are we now?

机译:虹膜介绍攻击检测:我们现在在哪里?

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As the popularity of iris recognition systems increases, the importance of effective security measures against presentation attacks becomes paramount. This work presents an overview of the most important advances in the area of iris presentation attack detection published in the recent two years. Newly-released, publicly-available datasets for development and evaluation of iris presentation attack detection are discussed. Recent literature can be seen to be broken into three categories: traditional "hand-crafted" feature extraction and classification, deep learning-based solutions, and hybrid approaches fusing both methodologies. Conclusions of modern approaches underscore the difficulty of this task. Finally, commentary on possible directions for future research is provided. (C) 2020 Published by Elsevier B.V.
机译:随着虹膜识别系统的普及,有效安全措施对演示攻击的重要性变得至高无上。这项工作概述了近两年发布的虹膜介绍攻击检测领域最重要的进展情况。讨论了用于开发和评估IRIS呈现攻击检测的新发布的公开可用数据集。最近的文献可以被视为分为三类:传统的“手工制作”特征提取和分类,基于深度学习的解决方案,以及融合两种方法的杂交方法。现代方法的结论强调了这项任务的难度。最后,提供了对未来研究的可能指示的评论。 (c)2020由elsevier b.v发布。

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