基于局部二值模式的人脸呈现攻击检测

Fei Peng, Le Qin, Min Long
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引用次数: 13

摘要

为了对抗人脸识别系统中的人脸呈现攻击,充分分析了真实人脸和伪人脸之间的颜色纹理差异,提出了局部二值模式的颜色共现(CCoLBP)来研究基于信道间的信息。基于呈现攻击的原理及其对人脸图像颜色成分的影响,提出了一种基于CCoLBP的人脸呈现攻击检测方案。将基于通道内的人脸纹理与CCoLBP特征相结合,表征了真实人脸与伪图像之间的颜色失真和纹理分布差异。有了这些特征,检测是通过使用Softmax分类器完成的。在5个公共数据库上进行了实验,实验结果和分析表明了CCoLBP算法的有效性,并能在跨数据库测试中取得良好的性能。它在具有实时性要求的人脸PAD应用中具有很大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CCoLBP: Chromatic Co-Occurrence of Local Binary Pattern for Face Presentation Attack Detection
To counter face presentation attack in face recognition system, the chromatic facial texture differences between the real faces and the facial artefacts are fully analyzed, and chromatic co-occurrence of local binary pattern (CCoLBP) is proposed to investigate the inter-channel based information. Based on the principle of presentation attack and its influence on color component of the face image, a face presentation attack detection (PAD) scheme based on CCoLBP is proposed. By combining intra-channel based facial texture and CCoLBP feature, the differences of color distortion and texture distribution between the real faces and the artefacts are characterized. With these features, the detection is accomplished by using a Softmax classifier. Experiments are done with 5 public databases, and the experimental results and analysis indicate the effectiveness of CCoLBP, and it can achieve good performance in cross-database testing. It has great potential in the application of face PAD with real-time requirement.
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