A Dynamic Multiple Watermarking Algorithm Based on DWT and HVS
ABSTRACT
In this paper, a dynamic robust multiple watermarking algorithm is proposed based on Discrete Wavelet Transform (DWT) and Human Visual System (HVS). Watermark image is transformed by Arnold transform. Original image is divided into blocks with 8 by 8 and each block is transformed by DWT. By adopting the Just Noticeable Difference (JND) of HVS and changing low frequency coefficients, binary string message can be embedded into the decomposed original image. Watermark can be extracted blindly. Experimental results have shown that the proposed watermarking has robust against many attacks such as JPEG compressing, cropping, additive noise, line removal, median filter and related attacks with sinStirMark.
In this paper, a dynamic robust multiple watermarking algorithm is proposed based on Discrete Wavelet Transform (DWT) and Human Visual System (HVS). Watermark image is transformed by Arnold transform. Original image is divided into blocks with 8 by 8 and each block is transformed by DWT. By adopting the Just Noticeable Difference (JND) of HVS and changing low frequency coefficients, binary string message can be embedded into the decomposed original image. Watermark can be extracted blindly. Experimental results have shown that the proposed watermarking has robust against many attacks such as JPEG compressing, cropping, additive noise, line removal, median filter and related attacks with sinStirMark.
Cite this paper
L. Zhang, X. Yan, H. Li and M. Chen, "A Dynamic Multiple Watermarking Algorithm Based on DWT and HVS," International Journal of Communications, Network and System Sciences, Vol. 5 No. 8, 2012, pp. 490-495. doi: 10.4236/ijcns.2012.58059.
L. Zhang, X. Yan, H. Li and M. Chen, "A Dynamic Multiple Watermarking Algorithm Based on DWT and HVS," International Journal of Communications, Network and System Sciences, Vol. 5 No. 8, 2012, pp. 490-495. doi: 10.4236/ijcns.2012.58059.
References
[1] S. W. Weng, et al., “Reversible Watermarking Based on Invariability and Adjustment on Pixel Pairs,” Signal Processing Letters, Vol. 15, 2008, pp. 721-724. doi:10.1109/LSP.2008.2001984 [2] S. Kapre Bhagyashri and M. Y. Joshi, “All Frequency Band DWT-SVD Robust Watermarking Technique for Color Images in YUV Color Space,” IEEE International Conference on CSAE, Vol. 3, 2011, pp. 295-299. [3] J. C. Patra, A. K. Kishore and C. Bornand, “Improved CRT-Based DCT Domain Watermarking Technique with Robustness against JPEG Compression for Digital Media Authentication,” 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, 9-12 October 2011, pp. 2940-2945, [4] S. Zhu and L. Jianming, “A Novel Adaptive Watermarking Scheme Based on Human Visual System and Particle Swarm Optimization,” Springer-Verlag, Berlin, 2009, pp. 136-146. [5] Y. Zhang, “Blind Watermark Algorithm Based on HVS and RBF Neural Network in DWT Domain,” WSEAS Transactions on Computers, Vol. 8, No. 1, 2009, pp. 174-183. [6] J. N. Yang, X. L. Zhou and Y. X. Ge, “A Robust Content-Based Digital Image Watermarking Technique,” 2010 Chinese Conference on CCPR, Chongqing, 21-23 October 2010. [7] A. Salama, R. Atta, R. Rizk and F. Wanes, “A Robust Digital Image Watermarking Technique Based on Wavelet Transform,” 2011 IEEE International Conference on System Engineering and Technology, Shah Alam, 27-28 June 2011, pp. 100-105. doi:10.1109/ICSEngT.2011.5993429 [8] S. Zhu and J. M. Liu, “A Novel Adaptive Watermarking Scheme Based on Human Visual System and Particle Swarm Optimization,” Springer-Verlag, Berlin, 2009, pp. 136-146. [9] P. Christine and W. J. Zeng, “Image-Adaptive Watermaking Using Visual Models,” IEEE Journal on Selected Areas in communications, Vol. 16, No. 4, 1998, pp. 525-539. doi:10.1109/49.668975 [10] K. X. Yi, “Research on Digital Image Encryption and Digital Watermarking,” Ph.D. Thesis, Zhejiang University, Hangzhou, 2001, pp. 89-105.
[1] S. W. Weng, et al., “Reversible Watermarking Based on Invariability and Adjustment on Pixel Pairs,” Signal Processing Letters, Vol. 15, 2008, pp. 721-724. doi:10.1109/LSP.2008.2001984 [2] S. Kapre Bhagyashri and M. Y. Joshi, “All Frequency Band DWT-SVD Robust Watermarking Technique for Color Images in YUV Color Space,” IEEE International Conference on CSAE, Vol. 3, 2011, pp. 295-299. [3] J. C. Patra, A. K. Kishore and C. Bornand, “Improved CRT-Based DCT Domain Watermarking Technique with Robustness against JPEG Compression for Digital Media Authentication,” 2011 IEEE International Conference on Systems, Man, and Cybernetics, Anchorage, 9-12 October 2011, pp. 2940-2945, [4] S. Zhu and L. Jianming, “A Novel Adaptive Watermarking Scheme Based on Human Visual System and Particle Swarm Optimization,” Springer-Verlag, Berlin, 2009, pp. 136-146. [5] Y. Zhang, “Blind Watermark Algorithm Based on HVS and RBF Neural Network in DWT Domain,” WSEAS Transactions on Computers, Vol. 8, No. 1, 2009, pp. 174-183. [6] J. N. Yang, X. L. Zhou and Y. X. Ge, “A Robust Content-Based Digital Image Watermarking Technique,” 2010 Chinese Conference on CCPR, Chongqing, 21-23 October 2010. [7] A. Salama, R. Atta, R. Rizk and F. Wanes, “A Robust Digital Image Watermarking Technique Based on Wavelet Transform,” 2011 IEEE International Conference on System Engineering and Technology, Shah Alam, 27-28 June 2011, pp. 100-105. doi:10.1109/ICSEngT.2011.5993429 [8] S. Zhu and J. M. Liu, “A Novel Adaptive Watermarking Scheme Based on Human Visual System and Particle Swarm Optimization,” Springer-Verlag, Berlin, 2009, pp. 136-146. [9] P. Christine and W. J. Zeng, “Image-Adaptive Watermaking Using Visual Models,” IEEE Journal on Selected Areas in communications, Vol. 16, No. 4, 1998, pp. 525-539. doi:10.1109/49.668975 [10] K. X. Yi, “Research on Digital Image Encryption and Digital Watermarking,” Ph.D. Thesis, Zhejiang University, Hangzhou, 2001, pp. 89-105.