具有多块LBP特征的面部区域的面部呈现攻击检测性能
Asuman Günay Yılmaz1, Uğur Turhal2, Vasif Nabiyev1
1Karadeniz Technical University, Trabzon, Turkey.
概括
面部呈现攻击 (FPA) 检测对于安全至关重要. 这项研究评估了面部区域,发现使用所有局部二进制模式 (LBP) 模式可以提高FPA检测性能,特别是当面部部分隐蔽时.
科学领域:
- 计算机科学 计算机科学
- 生物识别信息 生物识别信息
- 图像处理 图像处理
背景情况:
- 生物识别系统,特别是面部认证,容易受到面部呈现攻击 (FPA) 的影响.
- 越来越多的手术口罩影响了面部识别系统的性能,需要研究用于身份验证的替代面部区域.
- 现有的研究往往集中在眼部区域,促使对其他面部区域进行评估以检测FPA.
研究的目的:
- 为了研究面部呈现攻击 (FPA) 在各种面部区域的检测性能:宽脸,剪裁脸,眼睛,鼻子和嘴巴.
- 评估使用所有局部二进制模式 (LBP) 模式与仅使用统一的LBP模式来检测FPA的影响.
- 为了评估FPA检测的有效性,当整个脸是不可见的.
主要方法:
- 面部区域被细分和正常化.
- 使用多块局部二进制模式 (LBP) 提取纹理特征,同时考虑均和所有LBP模式.
- 主要组件分析 (PCA) 用于特征向量的维度减少.
- 支持矢量机器 (SVM) 用于真假分类.
主要成果:
- 与仅使用均模式相比,使用所有LBP模式显著提高了FPA检测性能.
- 跨多个数据集 (NUAA,CASIA,REPLAY-ATTACK,OULU-NPU) 的实验结果验证了拟议方法的有效性.
- 该研究表明,FPA检测是可行的,即使在使用有限的面部区域时也可以加强.
结论:
- 使用所有局部二进制模式 (LBP) 模式在面部呈现攻击 (FPA) 检测中比仅使用统一模式更有效.
- 拟议的方法,包括多块LBP特征和PCA,增强生物识别系统对FPA的稳定性.
- 这项研究为开发更安全的面部识别系统提供了宝贵的见解,特别是在面部部分可见性的场景中.
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