基于3D CNN的指纹通过光学连贯性断层扫描进行反伪造
Yilong Zhang1, Shichang Yu1, Shiliang Pu2
1College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China.
Heliyon
|October 9, 2023
概括
光学连贯断层扫描 (OCT) 为指纹防伪提供高分辨率的非侵入性成像. 使用OCT数据的新型3D卷积神经网络 (CNN) 方法与传统方法相比,显著提高了反伪造性能.
科学领域:
- 生物识别信息 生物识别信息
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 光学连贯断层扫描 (OCT) 提供了地下组织结构的非侵入性,高分辨率的成像.
- 指纹识别系统很容易受到使用人工指纹的假冒攻击.
- 内部指纹结构,包括汗腺,为增强安全提供独特的生物识别功能.
研究的目的:
- 建议和评估一种新的反伪造方法,用于使用OCT进行指纹识别.
- 利用来自OCT扫描的生物识别数据的3D空间连续性.
- 为了证明3D卷积神经网络 (CNN) 对于基于OCT的指纹防伪的有效性.
主要方法:
- 使用光学一致性断层扫描 (OCT) 获取内部指纹结构.
- 开发一个3D卷积神经网络 (CNN) 模型来分析OCT数据.
- 在自建和公共指纹数据集上训练和测试3D CNN模型.
- 将3D CNN方法与经典网络架构进行比较.
主要成果:
- 拟议的OCT指纹防伪方法表现出高精度.
- 3D CNN方法有效地利用了3D生物识别数据的空间连续性.
- 在反伪造实验中,3D CNN 策略的表现优于传统的网络模型.
结论:
- 海外技术是获得安全应用程序详细内部指纹结构的可行工具.
- 3D CNN对于分析OCT数据和增强指纹防伪能力是非常有效的.
- 拟议的方法为提高生物识别系统的安全性和可靠性提供了一个有希望的解决方案.
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