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CCoLBP: Chromatic Co-Occurrence of Local Binary Pattern for Face Presentation Attack Detection

机译:CColbp:面部呈现攻击检测的局部二进制模式的色彩共同发生

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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.
机译:为了对面部识别系统进行抗衡面呈现攻击,建议完全分析真实面和面部伪影之间的色面部质地差异,并且提出了局部二进制模式(CColbp)的彩色共发生以研究基于间的信息间的信息。基于呈现攻击原理及其对面部图像颜色分量的影响,提出了一种基于CColbp的面部呈现攻击检测(PAD)方案。通过组合基于沟道内的面部纹理和CColbp特征,特征在于真实面和人工制品之间的颜色失真和纹理分布的差异。利用这些功能,通过使用SoftMax分类器来完成检测。实验完成了5个公共数据库,实验结果和分析表明了Colbpp的有效性,它可以在跨数据库测试中实现良好的性能。它具有较大的潜力,可以使用实时要求。

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