Schur分解的快速零水印算法
|
摘要
为解决奇异值分解水印算法中所产生高虚警、鲁棒性不强以及安全性不高的问题,提出一种基于矩阵Schur分解的双重加密快速鲁棒零水印算法。该算法先将原始图像低频块进行矩阵Schur分解得到稳定值;提取Schur分解的块上三角矩阵对角线元素中含有最大能量元素的绝对值,并将其构造过渡矩阵;将该矩阵的平均值与每一个元素值进行比较生成感知哈希二值序列,构造特征矩阵;再将经过混沌映射加密的特征矩阵与斐波那契(Fibonacci)变换加密后的水印信息进行逻辑运算得到零水印;最后在第三方版权认证中心(intellectual property rights,IPR)完成注册。实验表明,在随机载体图像中所提取的水印NC值均在0.5以下,有效地解决高虚警问题;与基于整数小波变换的鲁棒零水印相比,抵抗噪声攻击的性能提高了2.43%;与时域水印算法相比,抵抗JPEG压缩攻击的性能提高了4.88%。
In order to solve the problems of high false alarm, poor robustness and security in the SVD(singular value decomposition) watermarking algorithms, this paper proposes a fast zero-watermarking algorithm with both the double encryption and strong robustness based on matrix Schur decomposition. Firstly, the matrix Schur decomposition is used on the low-frequency blocks of original images to obtain a stable value. Then, it extracts the absolute value of diagonal elements containing the largest energy elements of the upper triangular matrix of Schur decomposition block matrix so that it constructs a transition matrix. Next, to obtain the characteristic matrix, the average value of the matrix is compared with each element value to generate a perceptual Hash binary sequence. In addition, the chaotic map-encrypted feature matrix and the Fibonacci transform-encrypted watermark information are operated to obtain a zero-watermark. Finally, the registration is completed in the third party copyright certification center of IPR(intellectual property rights). Experimental results show that the NC value of watermark extracted from random carriers is less than 0.5, which can effectively solve the problem of high false alarm. Compared with the robust zero watermark based on integer wavelet transform, the performance of noise immunity is improved by2.43%. In contrast with the time-domain watermarking algorithm, the resistance to JPEG raises up to 4.88% in performance.
In order to solve the problems of high false alarm, poor robustness and security in the SVD(singular value decomposition) watermarking algorithms, this paper proposes a fast zero-watermarking algorithm with both the double encryption and strong robustness based on matrix Schur decomposition. Firstly, the matrix Schur decomposition is used on the low-frequency blocks of original images to obtain a stable value. Then, it extracts the absolute value of diagonal elements containing the largest energy elements of the upper triangular matrix of Schur decomposition block matrix so that it constructs a transition matrix. Next, to obtain the characteristic matrix, the average value of the matrix is compared with each element value to generate a perceptual Hash binary sequence. In addition, the chaotic map-encrypted feature matrix and the Fibonacci transform-encrypted watermark information are operated to obtain a zero-watermark. Finally, the registration is completed in the third party copyright certification center of IPR(intellectual property rights). Experimental results show that the NC value of watermark extracted from random carriers is less than 0.5, which can effectively solve the problem of high false alarm. Compared with the robust zero watermark based on integer wavelet transform, the performance of noise immunity is improved by2.43%. In contrast with the time-domain watermarking algorithm, the resistance to JPEG raises up to 4.88% in performance.
引文
[1] Zheng Q M, Zhang M M. Research on several algorithms of digital image watermarking[J]. Automation&Instrumentation,2017(9):38-39.
[2] Liu R Z, Tan T N. SVD based digital watermarking method[J]. Acta Electronica Sinica, 2001, 29(2):168-171.
[3] Xiong X G, Wang L. Improved reference watermarking scheme in DWT-SVD domain[J]. Computer Engineering and Applications, 2014, 50(7):75-79.
[4] Xiao Z J, Li N, Wang Y B, et al. Wavelet domain digital watermarking method based on watermark principal components[J]. Computer Applications and Software, 2016, 33(11):273-276.
[5] Rao Y R, Nagabhooshanam E. A novel image zero-watermarking scheme based on DWT-BN-SVD[C]//Proceedings of the International Conference on Information Communication and Embedded Systems, Chennai, Feb 27-28, 2014. Piscataway:IEEE, 2014:1-6.
[6] Mohammad A A. A new digital image watermarking scheme based on Schur decomposition[J]. Multimedia Tools&Applications, 2012, 59(3):851-883.
[7] Mohan B C, Swamy K V, Kumar S S. A comparative performance evaluation of SVD and Schur decompositions for image watermarking[C]//Proceedings of the International Conference on VLSI, Communication&Instrumentation,Kottayam, Apr 7-9, 2011. New York:Foundation of Computer Science, 2011:25-29.
[8] Liu F, Yang H Y, Su Q T. Color image blind watermarking algorithm based on Schur decomposition[J]. Application Research of Computers, 2017, 34(10):3085-3089.
[9] Wang X H, Sun Y Q. Region of interest based watermarking algorithm based on QR code and Schur decomposition[J].Journal of Optoelectronics·Laser, 2017, 28(4):419-426.
[10] Wen Q, Sun T F, Wang S X. Concept and application of zero-watermark[J]. Acta Electronica Sinica, 2003, 31(2):214-216.
[11] Sang J, Liao X F, Alam M S. Neural-network-based zerowatermark scheme for digital images[J]. Optical Engineering,2006, 45(9):097006.
[12] Cao H Q, Xiang H, Li X T, et al. A zero-watermarking algorithm based on DWT and chaotic modulation[C]//Proceedings of the Independent Component Analyses, Wavelets,Unsupervised Smart Sensors, and Neural Networks IV,Orlando, Apr 17, 2006. Bellingham:International Society for Optics and Photonics, 2006:624716.
[13] Kalker T, Haitsma J, Oostveen J C. Issues with digital watermarking and perceptual hashing[C]//Proceedings of the Multimedia Systems and Applications IV, Denver, Nov 12,2001. Bellingham:International Society for Optics and Photonics, 2001:189-198.
[14] Niu X M, Jiao Y H. An overview of perceptual hashing[J].Acta Electronica Sinica, 2008, 36(7):1405-1411.
[15] Li Y J, Li J B. DCT and perceptual hashing based to identify texture anti-counterfeiting tag[J]. Application Research of Computers, 2014, 31(12):3734-3737.
[16] Wang T. Digital image watermarking using dual-scrambling and singular value decomposition[C]//Proceedings of the International Conference on Computational Science and Engineering, and International Conference on Embedded and Ubiquitous Computing, Guangzhou, Jul 21-24, 2017. Washington:IEEE Computer Society, 2017:724-727.
[17] Su Q T. Research on blind watermarking scheme of digital color image[D]. Shanghai:East China University of Science and Technology, 2013.
[18] Su Q T. Color digital image blind watermarking technology[M]. Beijing:Tsinghua University Press, 2015.
[19] Yi J P, Liu P, Guo X. Digital watermarking algorithm based on matrix decomposition and chaotic scrambling[J]. Journal of Zhengzhou University(Natural Science Edition), 2013,45(2):50-53.
[20] Bayoudh I, Jabra S B, Zagrouba E. A robust video watermarking for real-time application[C]//LNCS 10617:Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems, Belgium, Sep 18-21, 2017.Berlin, Heidelberg:Springer, 2017:493-504.
[21] Xiao Z J, Zhang H, Chen H, et al. Zero-watermarking based on boost normed singular value decomposition and cellular neural network[J]. Journal of Image and Graphics, 2017, 22(3):288-296.
[22] Zeng W Q, Xiong X G. Robust zero watermarking algorithm based on integer wavelet transform[J]. Microelectronics&Computer, 2016, 33(4):97-101.
[23] Shen Z L, Kintak U. A novel image zero-watermarking scheme based on non-uniform rectangular[C]//Proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, Ningbo, Jul 9-12, 2017. Washington:IEEE Computer Society, 2017:78-82.
[1]郑秋梅,张萌萌.数字图像水印的主要几种算法研究[J].自动化与仪器仪表, 2017(9):38-39.
[2]刘瑞祯,谭铁牛.基于奇异值分解的数字图像水印方法[J].电子学报, 2001, 29(2):168-171.
[3]熊祥光,王力.一种改进的DWT-SVD域参考水印方案[J].计算机工程与应用, 2014, 50(7):75-79.
[4]肖振久,李南,王永滨,等.基于水印主成分的小波域数字水印方法[J].计算机应用与软件, 2016, 33(11):273-276.
[8]刘凡,杨洪勇,苏庆堂.基于矩阵Schur分解的彩色图像盲水印算法[J].计算机应用研究, 2017, 34(10):3085-3089.
[9]王晓红,孙业强.基于QR码和Schur分解的感兴趣区域水印算法[J].光电子·激光, 2017, 28(4):419-426.
[10]温泉,孙锬锋,王树勋.零水印的概念与应用[J].电子学报, 2003, 31(2):214-216.
[14]牛夏牧,焦玉华.感知哈希综述[J].电子学报, 2008, 36(7):1405-1411.
[15]李雨佳,李京兵.基于DCT和感知哈希的纹理防伪标签鉴别算法[J].计算机应用研究, 2014, 31(12):3734-3737.
[17]苏庆堂.基于盲提取的彩色图像数字水印算法的研究[D].上海:华东理工大学, 2013.
[18]苏庆堂.彩色图像数字盲水印技术[M].北京:清华大学出版社, 2015.
[19]易景平,刘鹏,郭欣.基于矩阵分解和混沌置乱的数字水印算法[J].郑州大学学报(理学版), 2013, 45(2):50-53.
[21]肖振久,张晗,陈虹,等.增强奇异值分解和细胞神经网络的零水印[J].中国图象图形学报, 2017, 22(3):288-296.
[22]曾文权,熊祥光.基于整数小波变换的鲁棒零水印算法[J].微电子学与计算机, 2016, 33(4):97-101.
[2] Liu R Z, Tan T N. SVD based digital watermarking method[J]. Acta Electronica Sinica, 2001, 29(2):168-171.
[3] Xiong X G, Wang L. Improved reference watermarking scheme in DWT-SVD domain[J]. Computer Engineering and Applications, 2014, 50(7):75-79.
[4] Xiao Z J, Li N, Wang Y B, et al. Wavelet domain digital watermarking method based on watermark principal components[J]. Computer Applications and Software, 2016, 33(11):273-276.
[5] Rao Y R, Nagabhooshanam E. A novel image zero-watermarking scheme based on DWT-BN-SVD[C]//Proceedings of the International Conference on Information Communication and Embedded Systems, Chennai, Feb 27-28, 2014. Piscataway:IEEE, 2014:1-6.
[6] Mohammad A A. A new digital image watermarking scheme based on Schur decomposition[J]. Multimedia Tools&Applications, 2012, 59(3):851-883.
[7] Mohan B C, Swamy K V, Kumar S S. A comparative performance evaluation of SVD and Schur decompositions for image watermarking[C]//Proceedings of the International Conference on VLSI, Communication&Instrumentation,Kottayam, Apr 7-9, 2011. New York:Foundation of Computer Science, 2011:25-29.
[8] Liu F, Yang H Y, Su Q T. Color image blind watermarking algorithm based on Schur decomposition[J]. Application Research of Computers, 2017, 34(10):3085-3089.
[9] Wang X H, Sun Y Q. Region of interest based watermarking algorithm based on QR code and Schur decomposition[J].Journal of Optoelectronics·Laser, 2017, 28(4):419-426.
[10] Wen Q, Sun T F, Wang S X. Concept and application of zero-watermark[J]. Acta Electronica Sinica, 2003, 31(2):214-216.
[11] Sang J, Liao X F, Alam M S. Neural-network-based zerowatermark scheme for digital images[J]. Optical Engineering,2006, 45(9):097006.
[12] Cao H Q, Xiang H, Li X T, et al. A zero-watermarking algorithm based on DWT and chaotic modulation[C]//Proceedings of the Independent Component Analyses, Wavelets,Unsupervised Smart Sensors, and Neural Networks IV,Orlando, Apr 17, 2006. Bellingham:International Society for Optics and Photonics, 2006:624716.
[13] Kalker T, Haitsma J, Oostveen J C. Issues with digital watermarking and perceptual hashing[C]//Proceedings of the Multimedia Systems and Applications IV, Denver, Nov 12,2001. Bellingham:International Society for Optics and Photonics, 2001:189-198.
[14] Niu X M, Jiao Y H. An overview of perceptual hashing[J].Acta Electronica Sinica, 2008, 36(7):1405-1411.
[15] Li Y J, Li J B. DCT and perceptual hashing based to identify texture anti-counterfeiting tag[J]. Application Research of Computers, 2014, 31(12):3734-3737.
[16] Wang T. Digital image watermarking using dual-scrambling and singular value decomposition[C]//Proceedings of the International Conference on Computational Science and Engineering, and International Conference on Embedded and Ubiquitous Computing, Guangzhou, Jul 21-24, 2017. Washington:IEEE Computer Society, 2017:724-727.
[17] Su Q T. Research on blind watermarking scheme of digital color image[D]. Shanghai:East China University of Science and Technology, 2013.
[18] Su Q T. Color digital image blind watermarking technology[M]. Beijing:Tsinghua University Press, 2015.
[19] Yi J P, Liu P, Guo X. Digital watermarking algorithm based on matrix decomposition and chaotic scrambling[J]. Journal of Zhengzhou University(Natural Science Edition), 2013,45(2):50-53.
[20] Bayoudh I, Jabra S B, Zagrouba E. A robust video watermarking for real-time application[C]//LNCS 10617:Proceedings of the International Conference on Advanced Concepts for Intelligent Vision Systems, Belgium, Sep 18-21, 2017.Berlin, Heidelberg:Springer, 2017:493-504.
[21] Xiao Z J, Zhang H, Chen H, et al. Zero-watermarking based on boost normed singular value decomposition and cellular neural network[J]. Journal of Image and Graphics, 2017, 22(3):288-296.
[22] Zeng W Q, Xiong X G. Robust zero watermarking algorithm based on integer wavelet transform[J]. Microelectronics&Computer, 2016, 33(4):97-101.
[23] Shen Z L, Kintak U. A novel image zero-watermarking scheme based on non-uniform rectangular[C]//Proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, Ningbo, Jul 9-12, 2017. Washington:IEEE Computer Society, 2017:78-82.
[1]郑秋梅,张萌萌.数字图像水印的主要几种算法研究[J].自动化与仪器仪表, 2017(9):38-39.
[2]刘瑞祯,谭铁牛.基于奇异值分解的数字图像水印方法[J].电子学报, 2001, 29(2):168-171.
[3]熊祥光,王力.一种改进的DWT-SVD域参考水印方案[J].计算机工程与应用, 2014, 50(7):75-79.
[4]肖振久,李南,王永滨,等.基于水印主成分的小波域数字水印方法[J].计算机应用与软件, 2016, 33(11):273-276.
[8]刘凡,杨洪勇,苏庆堂.基于矩阵Schur分解的彩色图像盲水印算法[J].计算机应用研究, 2017, 34(10):3085-3089.
[9]王晓红,孙业强.基于QR码和Schur分解的感兴趣区域水印算法[J].光电子·激光, 2017, 28(4):419-426.
[10]温泉,孙锬锋,王树勋.零水印的概念与应用[J].电子学报, 2003, 31(2):214-216.
[14]牛夏牧,焦玉华.感知哈希综述[J].电子学报, 2008, 36(7):1405-1411.
[15]李雨佳,李京兵.基于DCT和感知哈希的纹理防伪标签鉴别算法[J].计算机应用研究, 2014, 31(12):3734-3737.
[17]苏庆堂.基于盲提取的彩色图像数字水印算法的研究[D].上海:华东理工大学, 2013.
[18]苏庆堂.彩色图像数字盲水印技术[M].北京:清华大学出版社, 2015.
[19]易景平,刘鹏,郭欣.基于矩阵分解和混沌置乱的数字水印算法[J].郑州大学学报(理学版), 2013, 45(2):50-53.
[21]肖振久,张晗,陈虹,等.增强奇异值分解和细胞神经网络的零水印[J].中国图象图形学报, 2017, 22(3):288-296.
[22]曾文权,熊祥光.基于整数小波变换的鲁棒零水印算法[J].微电子学与计算机, 2016, 33(4):97-101.