计算机科学 ›› 2021, Vol. 48 ›› Issue (6A): 443-447.doi: 10.11896/jsjkx.200900207

• 信息安全 • 上一篇    下一篇

噪声环境下的人脸防伪识别算法研究

卓雅倩, 欧博   

  1. 湖南大学信息科学与工程学院 长沙410082
  • 出版日期:2021-06-10 发布日期:2021-06-17
  • 通讯作者: 欧博(oubo@hnu.edu.cn)
  • 作者简介:zhuoyq@hnu.edu.cn
  • 基金资助:
    国家自然科学基金(61502160);湖南省自然科学基金青年项目(2018JJ3078)

Face Anti-spoofing Algorithm for Noisy Environment

ZHUO Ya-qian, OU Bo   

  1. College of Computer Science and Electronic Engineering,Hunan University,Changsha 410082,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:ZHUO Ya-qian,born in 1997,postgra-duate.Her main research interests include information security and image processing.
    OU Bo,born in 1985,Ph.D,associate professor,Ph.D supervisor.His main research interests include information security and digital watermarking.
  • Supported by:
    National Natural Science Foundation of China(61502160) and Hunan Provincial Natural Science Foundation of China(2018JJ3078).

摘要: 智能时代,人脸识别算法是智能身份认证的关键支撑技术之一,在门禁、手机解锁和金融支付领域有着重要应用。而人脸防伪识别则是用来增强其识别安全性,对抗伪造人脸攻击和鉴别真实人脸的防御性技术,相关研究颇多。其中基于LBP(local binary pattern)的人脸防伪算法综合性能较好,但是现有算法在噪声场景下的识别性能还难以令人满意。为此,文章提出基于相邻像素对的PLBP(pairwise local binary pattern)特征模式,通过充分挖掘像素对之间的相关性,来改进噪声环境下的算法性能。相比于LBP,所提算法以相邻像素对均值为基准与邻域其余像素比较生成二进制模式,从而能够利用像素对间的空间相关性来获取新的人脸特征。实验结果表明,该算法与主流LBP算法相比性能有所提升。其在无噪声条件下准确率接近了95.05%,在有高斯噪声环境下则能有效降低性能损失。相比其他算法在高斯噪声环境下的准确率下降情况,所提算法表现稳定,有着较好的鲁棒性。

关键词: 人脸防伪检测, 像素对局部二值模式特征, 支持向量机

Abstract: In the era of intelligent,face recognition algorithm is one of the key technologies for smart identity authentication,and widely used in the fields of access control,mobile phone unlocking,and financial payment.Face anti-spoofing recognition is used to identify the real face and resist the fake face attacks.Among the existing methods,local binary pattern(LBP) can provide a good anti-spoofing performance in practice,but its recognition performance in noisy scenes can be improved.For this reason,we proposed a pairwise local binary pattern (PLBP) based on adjacent pixel pairs,which can improve the performance in noisy environments by exploiting the correlations between pixel pairs.Compared with LBP-based methods,the proposed algorithm compared the mean value of adjacent pixel pairs with neighboring pixels to generate a binary pattern,so that the spatial correlations between pixel pairs can be used to obtain more facial features.Experiment results show that the performance of the proposed method is better than the current mainstream LBP-based methods,the accuracy rate is nearly 95.05% under noise-free conditions.Our method also can reduce performance loss under Gaussian noise environment and provide a stronger robustness.

Key words: Face anti-spoofing, Pairwise local binary pattern, Support vector machine

中图分类号: 

  • TP399
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