Security algorithm of face recognition based on local binary pattern and random projection

Zhou Lingli, Lai Jianghuang
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引用次数: 3

Abstract

With the growing applications of biometrics, there are many concerns about the security and privacy of the biometrics data. This paper proposes a security algorithm of face recognition, which bases on the local binary pattern (LBP) and random projection. Feature extraction is first performed on face images by LBP operator. Random projection is done using the random matrix which is generated by user specific key. All the above successive procedures produce the cancelable and non-invertible feature data, which is stored in template databases and can achieve the protection of biometrics data. In extensive experiments with publicly available face datasets ORL, YALE and FERET, higher recognition accuracy is reached, which demonstrates that the proposed approach is able to not only protect the biometrics data, but also is robust to various complex conditions, such as illumination, changes in the pose and expression, etc.
基于局部二值模式和随机投影的人脸识别安全算法
随着生物识别技术的应用日益广泛,人们对生物识别数据的安全性和隐私性提出了许多担忧。提出了一种基于局部二值模式和随机投影的人脸识别安全算法。首先利用LBP算子对人脸图像进行特征提取。随机投影是利用用户指定密钥生成的随机矩阵来实现的。上述连续的步骤产生可取消和不可逆转的特征数据,这些特征数据存储在模板数据库中,可以实现对生物特征数据的保护。在ORL、YALE和FERET等公开的人脸数据集上进行了大量的实验,取得了较高的识别精度,表明该方法不仅能够保护生物特征数据,而且对光照、姿态和表情变化等各种复杂条件具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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