摘要
针对单一特征模板保护算法效果较差以及存储前对模板保护不足等问题,提出一种多特征融合的人脸模板保护方法。该方法利用两种特征提取算法提取人脸不同的特征,实现多特征的融合保护,并在特征变换阶段将两种特征分别作为两个掩模,使用双随机相位掩模技术对原始图像进行加密。在存储前利用密钥生成思想从图像中直接获取密钥,并结合伴随矩阵性质,设计了一种改进分块幻方变换的置乱算法。为验证算法性能,采用ORL和EYaleB两个人脸数据库分别进行测试。结果表明,置乱算法的置乱度在ORL数据库可以达0.0194,在EYaleB数据库上可达0.0187,所提模板保护方法的识别率可分别达97.12%和96.90%。模板保护的三大特性不可逆性、可撤销性和不可链接性均表现良好。
Herein,we propose a face template protection method based on multifeature fusion to solve the problems of the poor effect of a single feature template protection algorithm and insufficient template protection before storage.In this method,two feature extraction algorithms were employed to extract different face features to achieve multifeature fusion protection.Furthermore,both features were used as masks in the feature transformation stage.The original image was encrypted using the double random phase mask technology.Before storage,we designed an improved scrambled algorithm based on partitioned magic square transformation to obtain the key from the image using the idea of key generation and properties of the adjoint matrix.To verify the performance of the algorithm,two face databases,ORL and EYaleB,were used.The results show that the scrambling degree of the scrambled algorithm can reach 0.0194 and 0.0187 in the ORL and EYaleB databases,respectively,and the recognition rate of the proposed template protection method reaches 97.12%and 96.90%,respectively.The three characteristics of template protection,namely,irreversibility,revocability,and unlinkability,perform well.
作者
张波
佟玉强
Zhang Bo;Tong Yuqiang(College of Computer Science and Technology,Shenyang University of Chemical Technology,Shenyang 110142,Liaoning,China;Liaoning Key Laboratory of Industrial Intelligence Technology on Chemical Process,Shenyang 110142,Liaoning,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2022年第18期205-212,共8页
Laser & Optoelectronics Progress
基金
辽宁省教育厅科学研究项目(LJ2020023)
省博士科研启动基金(2019-BS191)。
关键词
模板保护
多特征
双随机相位编码
幻方变换
template protection
multifeatures
double random phase encoding
magic square transformation
