Internal Structure Attention Network for Fingerprint Presentation Attack Detection From Optical Coherence Tomography
Internal Structure Attention Network for Fingerprint Presentation Attack Detection From Optical Coherence Tomography
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DOI：
10.1109/tbiom.2023.3293910
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发表时间：
2023-03
期刊：
影响因子：
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通讯作者：
Hao Sun;Yilong Zhang;Peng Chen;Haixia Wang;Ronghua Liang
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文献类型：
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作者：
Hao Sun;Yilong Zhang;Peng Chen;Haixia Wang;Ronghua Liang
作为一种非侵入性光学成像技术，光学相干断层扫描（OCT）已被证明在自动指纹识别系统（AFRS）应用中具有广阔的前景。基于OCT的指纹呈现攻击检测（PAD）已经提出了多种方法。然而，考虑到PA样本的复杂性和多样性，在有限的PA数据集上提高泛化能力是极具挑战性的。为了解决这个问题，本文提出了一种新的监督学习的PAD方法，表示为内部结构注意PAD（ISAPAD）。ISAPAD应用先前的知识指导网络培训。ISAPAD中的双分支结构不仅可以从OCT图像中学习全局特征，还可以集中学习来自内部结构注意模块（ISAM）的分层结构特征。简单而有效的ISAM使网络能够从嘈杂的OCT体积数据中获得专门属于Bonafide的分层分割特征。通过整合有效的培训策略和PAD分数生成规则，ISAPAD即使在培训数据有限的情况下也能确保可靠的PAD性能。大量的实验和可视化分析证实了所提出的方法的有效性OCT PAD。
As a non-invasive optical imaging technique, optical coherence tomography (OCT) has proven promising for automatic fingerprint recognition system (AFRS) applications. Diverse approaches have been proposed for OCT-based fingerprint presentation attack detection (PAD). However, considering the complexity and variety of PA samples, it is extremely challenging to increase the generalization ability with the limited PA dataset. To solve the challenge, this paper presents a novel supervised learning-based PAD method, denoted as internal structure attention PAD (ISAPAD). ISAPAD applies prior knowledge to guide network training. Specifically, the proposed dual-branch architecture in ISAPAD can not only learn global features from the OCT images, but also concentrate on the layered structure feature which come from the internal structure attention module (ISAM). The simple yet effective ISAM enables the network to obtain layered segmentation features exclusively belonging to Bonafide from noisy OCT volume data. By incorporating effective training strategies and PAD score generation rules, ISAPAD ensures reliable PAD performance even with limited training data. Extensive experiments and visualization analysis substantiate the effectiveness of the proposed method for OCT PAD.