结构特征下的可撤销人脸识别  

Cancelable face recognition with fusion of structural features

作　　者：孙浩浩 邵珠宏[1] 尚媛园[1] 陈滨 赵晓旭[1] Sun Haohao;Shao Zhuhong;Shang Yuanyuan;Chen Bin;Zhao Xiaoxu(College of Information Engineering,Capital Normal University,Beijing 100048,China;College of Mathematics Physics and Information Engineering,Jiaxing 314001,China)

机构地区：[1]首都师范大学信息工程学院,北京100048 [2]嘉兴学院数理与信息工程学院,嘉兴314001

出　　处：《中国图象图形学报》2020年第12期2553-2562,共10页Journal of Image and Graphics

基　　金：国家自然科学基金项目(61876112,61601311);北京市优秀人才资助项目(2016000020124G088);北京市教委科研计划项目(SQKM201810028018,KM201910028018)。

摘　　要：目的相对于其他生物特征识别技术,人脸识别具有非接触、不易察觉和易于推广等特点,在公共安全和日常生活中得到广泛应用。在移动互联网时代,云端人脸识别可以有效地提高识别精度,但是需要将大量的人脸数据上传到第三方服务器。由于人的面部特征是唯一的,一旦数据库泄露就会面临模板攻击和假冒攻击等安全威胁。为了保证人脸识别系统的安全性并提高其识别率,本文提出一种融合人脸结构特征的可撤销人脸识别算法。方法首先,对原始人脸图像提取结构特征作为虚部分量,与原始人脸图像联合构建复数矩阵并通过随机二值矩阵进行置乱操作。然后,使用2维主成分分析方法将置乱的复数矩阵映射到新的特征空间。最后,采用基于曼哈顿距离的最近邻分类器计算识别率。结果在4个不同人脸数据库上的实验结果表明,原始人脸图像和结构特征图像经过随机二值矩阵置乱后,人眼无法察觉出有用的信息且可以重新生成,而且融合方差特征后,在GT(Georgia Tech)、NIR(Near Infrared)、VIS(Visible Light)和YMU(You Tu Be Makeup)人脸数据库上,平均人脸识别率分别提高了4.9%、2.25%、2.25%和1.98%,且平均测试时间均在1.0 ms之内,表明该算法实时性强,能够满足实际应用场景的需求。结论本文算法可在不影响识别率的情况下保证系统的安全性,满足可撤销性。同时,融合结构特征丰富了人脸信息的表征,提高了人脸识别系统的识别率。Objective Along with the wide usage of various digital image processing hardware and software and the continuous advancements in the field of computer vision,biometric recognition has been introduced to solve identification problems in people’s daily lives and has been applied in the fields of finance,education,healthcare,and social security,among others.Compared with iris,palm print,and other biometric recognition technologies,face recognition has received the most attention due to its special characteristics(e.g.,on-contact,imperceptible,and easy to promote).Given the wide usage of mobile Internet,cloud face recognition can achieve high recognition accuracy requires a large amount of face data to be uploaded to a third-party server.On the one hand,face images may reflect one’s private information,such as gender,age,and health status.On the other hand,given that each person has unique facial features,hacking into face image databases may expose people to threats,including template and fake attacks.Therefore,how to boost the privacy and security of face images has become a core issue in the field of biometric recognition.Among the available biometric template protection methods,the transform-based method can simultaneously satisfy multiple criteria of biometric template protection and is presently considered the most typical cancelable biometric algorithm.The protected biometric template is obtained via anoninvertible transformation of the original biometric that is saved in a database.When this biometric template is attacked or threatened,a new feature template can be reissued to replace the previous template by modifying the external factors.To guarantee the security of the face recognition system and improve its recognition rate,this paper investigates a cancelable face recognition algorithm that integrates the structural features of the human face.Method First,structural features are extracted from the original face image by using its gradient,local binary pattern,and local variance.By taking the original

关 键 词：可撤销人脸识别 随机二值矩阵 2维主成分分析 人脸结构特征 复数矩阵 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]