综合资源展示 综合资源展示

最小化 最大化
«返回

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

  • 详细信息
标题: Two-level image authentication by two-step phase-shifting interferometry and compressive sensing
资源摘要: Publication date: January 2018
Source:Optics and Lasers in Engineering, Volume 100

Author(s): Xue Zhang, Xiangfeng Meng, Yongkai Yin, Xiulun Yang, Yurong Wang, Xianye Li, Xiang Peng, Wenqi He, Guoyan Dong, Hongyi Chen

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.





资源原始URL http://rss.sciencedirect.com/action/redirectFile?&zone=main¤tActivity=feed&usageType=outward&url=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%3F_ob%3DGatewayURL%26_origin%3DIRSSSEARCH%26_method%3DcitationSearch%26_piikey%3DS0143816617305201%26_version%3D1%26md5%3D96b9cff83cca1559465d25d562babb3a
资源来源机构: Elsevier
资源来源机构URL: http://rss.sciencedirect.com/getMessage?registrationId=JDGJJEGKQFGSKEGNLDHNJKHNJHIJLHKQSEIOJMJPSO
来源机构所属国家: 其他
来源机构性质:
您还没有登录。 请先登录再使用本系统。
您还没有登录。 请先登录再使用本系统。