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IrisGuard: Image Forgery Detection for Iris Anti-spoofing
Zhuo, Wenqi1,2; Wang, Wei2; Zhang, Hui3; Dong, Jing2
2022-11-03
会议名称16th Chinese Conference on Biometric Recognition (CCBR2022)
卷号13628
页码602–612
会议日期2022.12.11-2022.12.13
会议地点Beijing
摘要

With the development of generative models, new types of fake iris have emerged. Distinguished from traditional spoofing means caused by cosmetic contact lenses, such iris images are realistic and easily accessible, which poses a threat to privacy protection and information security. In this paper, we are the first to study iris forgery detection method that can simultaneously defend against contact lenses based or GAN-generated spoofing attacks. Through multi-model ensemble, we design a simple but effective detection framework. The backbone part of our method consists of three CNN networks, including ResNet-18, EfficientNet-B0 and ConvNeXt-tiny. We conduct experiments on three public iris datasets and a great deal of StyleGAN-generated iris images which are collected by ourselves. The proposed method has been proved to be effective on the detection of various iris forgeries, and it has the state-of-the-art performances.

关键词iris anti-spoofing image forgery detection privacy protection
DOIDOI: 10.1007/978-3-031-20233-9_61
收录类别EI
语种英语
是否为代表性论文
七大方向——子方向分类生物特征识别
国重实验室规划方向分类视觉信息处理
是否有论文关联数据集需要存交
引用统计
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/51850
专题模式识别实验室
通讯作者Wang, Wei
作者单位1.School of Artificial Intelligence, University of Chinese Academy of Sciences
2.CRIPAC & NLPR, Institute of Automation, Chinese Academy of Sciences
3.Beijing IrisKing Co., Ltd.
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
GB/T 7714
Zhuo, Wenqi,Wang, Wei,Zhang, Hui,et al. IrisGuard: Image Forgery Detection for Iris Anti-spoofing[C],2022:602–612.
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