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山东大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (3): 25-33.doi: 10.6040/j.issn.1672-3961.0.2017.408

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基于SVD和DCNN的彩色图像多功能零水印算法

赵彦霞1,2, 王熙照1,3*   

  1. 1. 河北大学管理学院, 河北 保定 071002;2. 河北经贸大学信息技术学院, 河北 石家庄 050061;3. 深圳大学计算机与软件学院, 广东 深圳 518060
  • 收稿日期:2017-05-17 出版日期:2018-06-20 发布日期:2017-05-17
  • 通讯作者: 王熙照(1963— ),男,教授,博士,主要研究方向为机器学习,模式识别. E-mail:xizhaowang@ieee.org E-mail:zyxa6@126.com
  • 作者简介:赵彦霞(1970— ),女,讲师,博士研究生,主要研究方向为不确定知识管理和机器学习,数字水印,信息处理等. E-mail:zyxa6@126.com
  • 基金资助:
    国家自然科学基金资助项目(71371063,61672205);河北省应用基础研究计划重点基础研究资助项目(16960314D);河北省科技计划资助项目(15454704D);河北省人力资源社会保障科研合作课题资助项目(JRSHZ-2016-07038);深圳市科技计划资助项目(JCYJ20150324140036825)

Multipurpose zero watermarking algorithm for color image based on SVD and DCNN

ZHAO Yanxia1,2, WANG Xizhao1,3*   

  1. 1. College of Management, Hebei University, Baoding 071002, Hebei, China;
    2. College of Information &
    Technology, Hebei University of Economics and Business, Shijiazhuang 050061, Hebei, China;
    3. College of Computer Science &
    Software Engineering, Shenzhen University, Shenzhen 518060, Guangdong, China
  • Received:2017-05-17 Online:2018-06-20 Published:2017-05-17

摘要: 为了对彩色图像进行版权保护和篡改定位,提出一种基于奇异值分解(singular value decomposition, SVD)和深度卷积神经网络(deep convolutional neural network, DCNN)的彩色图像多功能零水印算法。将原始RGB彩色图像转换成YCbCr彩色图像,对原始图像的Y、Cb、Cr通道离散小波变换得到的系数矩阵进行奇异值分解,得到DCNN的输入矩阵,从DCNN输出层的输入矩阵中获取原始图像信息矩阵,生成零鲁棒水印图像。从Y通道小波变换得到的低频子带系数矩阵中获取原始图像信息矩阵,生成零半脆弱水印图像。试验结果证明,提出的算法不但有效,而且对强度较大的常见攻击有较好的抵抗能力。

关键词: 版权保护, 篡改定位, 深度卷积神经网络, 多功能零水印, 奇异值分解, 离散小波变换

Abstract: A multipurpose zero watermarking algorithm for color image based on SVD(singular value decomposition)and DCNN(deep convolutional neural network)were proposed for the copyright protection and tamper location of color image. The original RGB color image was transformed into YCbCr color image. The Y channel, Cb channel and Cr channel were transformed by DWT(discrete wavelet transform), some matrices were got through decomposing the coefficient matrices by SVD and got the inputs matrices of DCNN. The information matrix of original image was got from the inputs matrix of output layer of DCNN and was used to generate zero robust watermarking image. The information matrix was got from the coefficient matrix of low frequency subband through the DWT of Y channel and was used to generate the zero semi-fragile watermarking image. The experimental results showed that the algorithm was not only efficient but also had good resistance to the strong common attacks.

Key words: tamper location, singular value decomposition, multipurpose zero watermarking, discrete wavelet transform, copyright protection, deep convolutional neural network

中图分类号: 

  • TP391
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