An Efficient Digital Watermarking Technique for Color Images Using Directional Transforms
Abstract
This paper is concerned with a digital watermarking technique for color images based on directional transforms. Different from the traditional watermarking schemes which embed the watermarks into the spatial domain or frequency domain of the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT), this paper investigates the performance of the watermarking schemes using the Fast Discrete Curvelet Transforms (FDCT) and Contourlet Transform (CT). We evaluate the performance of the watermarking schemes using the directional transforms on a standard database of color images in terms of invisibility and robustness. The performance metrics are measured by Peak Signal-to-Noise Ratio (PSNR), Normalized Correlation (NC), Structural SIMilarity (SSIM) and required time for extracting and embedding process. The experimental results reveal that watermarking schemes in the directional transform domains outperform the other schemes in DWT domains.
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References
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[2] S. Ranjbar, F. Zargari, and M. Ghanbari. A highly robust two-stage contourlet-based digital image watermarking method. Signal Processing: Image Communication, 28(10):1526 – 1536, 2013.
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[28] M. N. Do and M. Vetterli. Contourlets: a directional multiresolution image representation. In Image Processing. 2002. Proceedings. 2002 International Conference on, volume 1, pages I–357–I–360 vol.1, 2002.
[29] Z. Y. Zhang, W. Huang, J. L. Zhang, H. Y. Yu, and Y. J. Lu. Digital image watermark algorithm in the curvelet domain. In 2006 International Conference on Intelligent Information Hiding and Multimedia, pages 105–108, Dec 2006.
[30] C. Deng, H. Zhu, and S. Wang. Curvelet domain watermark detection using alpha-stable models. In Information Assurance and Security, 2009. IAS ’09. Fifth International Conference on, volume 1, pages 313–316, Aug 2009.
[31] H. Song and J. Gu. Curvelet based adaptive watermarking for images. In Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on, pages 1101–1105, Dec 2012.
[32] H. Thai-Duy, I. Kei, H. Harak, Y. W. Chen, Y. Nagata, and Z. Nakao. Curvelet-domain image watermarking based on edge-embedding, pages 311–317. Springer Berlin Heidelberg, Berlin, Heidelberg, 2007.
[33] F. Ji, D. Huang, and et al. Robust curvelet-domain image watermarking based on feature matching. International Journal of Computer Mathematics, 88(18):39313941, 2011.
[34] J. Xu, H. Pang, and J. Zhao. Digital image watermarking algorithm based on fast curvelet transform. Journal of Software Engineering and Applications, 2010.
[35] N. R. Brinta and P. R. Bipin. A contourlet domain watermarking algorithm. International Journal of Image Processing and Vision Sciences (IJIPVS), 2012.
[36] S. Masaebi and A. M. E. Moghaddam. A new approach for image hiding based on contourlet transform. International Journal of Electrical and Computer Engineering (IJECE), 2(5):699–708, October 2012.
[37] K. N. Mahesh, T. Manikandan, and G. V. Saptha. Non-blind image watermarking using contourlet transform. Indian Journal of Computer Science and Engineering (IJCSE), 2(1):31–38, 2011.
[38] C. Qin and X. Wen. A novel digital watermarking algorithm in contourlet domain. Journal of information & computational science, 11(2):519, 2014.
[39] S. A. Hosseini and S. Ghofrani. Digital watermarking based on contourlet-svd. Majlesi Journal of Electrical Engineering, 8(1), 2013.
[40] Y. Anusha and K. Veeraswamy. An improved contourlet transform technique for image watermarking. International Journal of Research in Computer and Communication Technology, 22(11):1128–1132, 2013.
[41] H. Bi, X. Li, and Y. Zhang. A novel hvs-based watermarking scheme in contourlet transform domain. Indonesian Journal of Electrical Engineering and Computer Science, 11(12):7516 7524, 2013.
[42] H. Sadreazami, M. O. Ahmad, and M. N. S. Swamy. A study of multiplicative watermark detection in the contourlet domain using alpha-stable distributions. IEEE Transactions on Image Processing, 23(10):4348–4360, Oct 2014.
[43] Z.-W. Shen and F.-C. Liao. Adaptive watermark algorithm based fast curvelet transform. In Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, Hong Kong, 2008.
[44] E. Candes, L. Demanet, D. Donoho, and L. Ying. Fast discrete curvelet transforms. Multiscale Modeling & Simulation, 5(3):861–899, 2006.
[45] E. J. Candes and D. L. Donoho. Curvelets and curvilinear integrals, 2000. 10 JOURNAL OF SCIENCE AND TECHNOLOGY: ISSUE ON INFORMATION AND COMMUNICATIONS TECHNOLOGY, VOL. 3, NO. 2, DECEMBER 2017
[46] E. J. Candes and D. L. Donoho. New tight frames of curvelets and optimal representations of objects with piecewise c2 singularities. Communications on Pure and Applied Mathematics, 57(2):219–266, 2004.
[47] T. Le-Tien, K. Le-Cao, and C. Bui-Thu. An improvement of curvelet based super-resolution image processing implemented on arm at91sam9rl. In 2013 International Conference on Advanced Technologies for Communications (ATC 2013), pages 380–385, Oct 2013.
[48] D. D. Y. Po and M. N. Do. Directional multiscale modeling of images using the contourlet transform. IEEE Transactions on Image Processing, 15(6):1610–1620, June 2006.
[49] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: From error visibility to structural similarity. IEEE Transactios on Image Processing, 13(14):600–612, 2004.
[2] S. Ranjbar, F. Zargari, and M. Ghanbari. A highly robust two-stage contourlet-based digital image watermarking method. Signal Processing: Image Communication, 28(10):1526 – 1536, 2013.
[3] A. Boho, G. Van Wallendael, A. Dooms, J. De Cock, G. Braeckman, P. Schelkens, B. Preneel, and R. Van de Walle. End-to-end security for video distribution: The combination of encryption, watermarking, and video adaptation. IEEE
Signal Processing Magazine, 30(2):97–107, March 2013.
[4] N. Nikolaidis and I. Pitas. Robust image watermarking in the spatial domain. Signal Processing, 66(3):385 – 403, 1998.
[5] M. El-Gayyar and J. von zur Gathen. Watermarking techniques spatial domain. Technical report, University of Bonn Germany, 2006.
[6] H. Y. Leung, L. M. Cheng, and L. L. Cheng. A robust watermarking scheme using selective curvelet coefficients. International Journal ofWavelets, Multiresolution and Information Processing, 07(02):163–181, 2009.
[7] S. C. Nguyen, K. H. Ha, and H. M. Nguyen. A new image watermarking scheme using contourlet transforms. In The 3nd International Conference on Information Technology, Computer, And Electrical Engineering ( ICITACEE 2016 ), 2016.
[8] Y. RaghavenderRao, Dr. E. Nagabhooshanam, and et al. Image watermarking using hybrid wavelets and directional filter banks. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 2012.
[9] Y. RaghavenderRao, Dr.E.Nagabhooshanam, and P. Nikhil. Directional based watermarking scheme using a novel data embedding approach. Advanced Computing: An International Journal ( ACIJ ), 2012.
[10] S. C. Nguyen, K. H. Ha, and H. M. Nguyen. Digital image watermarking in spatial and transform domain: a survey and improved ppproach. In 2015 International Symposium on Electrical and Electronic Engineering (ISEE2015), 2015.
[11] X. Zhang and Y. Yang. A geometric distortion resilient image watermark algorithm based on dft- svd. In Computer Engineering, 2006.
[12] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon. Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing, 6(12):1673–1687, Dec 1997.
[13] S. Khalighi, P. Tirdad, and H. Rabiee. A contourlet-based image watermarking scheme with high resistance to removal and geometrical attacks. EURASIP Journal on Advances in Signal Processing, 2010(1):540723, 2010.
[14] S. A. Hosseini and S. Ghofrani. A wavelet tour of signal processing. 2nd ed., 1999.
[15] A. Skodras, C. Christopoulos, and T. Ebrahimi. The jpeg 2000 still image compression standard. IEEE Signal Processing Magazine, 18(5):36–58, Sep 2001.
[16] M. N. Do and M. Vetterli. The contourlet transform: an efficient directional multiresolution image representation. IEEE Transactions on Image Processing, 14(12):2091–2106, Dec 2005.
[17] J. Fadili and J.-L. Starck. Curvelets and Ridgelets, pages 1718–1738. Springer New York, New York, NY, 2009.
[18] J. G. Daugman. Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research, 20(10):847 – 856, 1980.
[19] A. B. Watson. The cortex transform: Rapid computation of simulated neural images. Computer Vision, Graphics, and Image Processing, 39(3):311 – 327, 1987.
[20] E. P. Simoncelli,W.T Freeman, E.H. Adelson, and D.J. Heeger. Shiftable multi-scale transforms. IEEE Trans. Information Theory, 1992.
[21] J.-P. Antoine, P. Carrette, R. Murenzi, and B. Piette. Image analysis with two-dimensional continuous wavelet transform. Signal Processing, 31(3):241 – 272, 1993.
[22] F. G. Meyer and R. R. Coifman. Brushlets: A tool for directional image analysis and image compression. Applied and Computational Harmonic Analysis, 4(2):147–187, 1997.
[23] N. Kingsbury. Complex wavelets for shift invariant analysis and filtering of signals. Applied and Computational Harmonic Analysis, 10(3):234 – 253, 2001.
[24] E. J. Candes and D.L. Donoho. Ridgelets: the key to high dimensional intermittency? Philosophical Transactions of the Royal Society of London A, page 24952509, 1999.
[25] E. J. Candes. Ridgelets: theory and applications. PhD thesis, Stanford University, 1998.
[26] E. J. Candes and D. L. Donoho. Curvelets: A surprisingly effective nonadaptive representation for objects with edges. In Vanderbilt University Press, Nashville, TN. ISBN. 0-8265-1357-3., 2000.
[27] M.N. Do and M. Vetterli. 4 - contourlets. In Grant V.Welland, editor, Beyond Wavelets, volume 10 of Studies in Computational Mathematics, pages 83 – 105. Elsevier, 2003.
[28] M. N. Do and M. Vetterli. Contourlets: a directional multiresolution image representation. In Image Processing. 2002. Proceedings. 2002 International Conference on, volume 1, pages I–357–I–360 vol.1, 2002.
[29] Z. Y. Zhang, W. Huang, J. L. Zhang, H. Y. Yu, and Y. J. Lu. Digital image watermark algorithm in the curvelet domain. In 2006 International Conference on Intelligent Information Hiding and Multimedia, pages 105–108, Dec 2006.
[30] C. Deng, H. Zhu, and S. Wang. Curvelet domain watermark detection using alpha-stable models. In Information Assurance and Security, 2009. IAS ’09. Fifth International Conference on, volume 1, pages 313–316, Aug 2009.
[31] H. Song and J. Gu. Curvelet based adaptive watermarking for images. In Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on, pages 1101–1105, Dec 2012.
[32] H. Thai-Duy, I. Kei, H. Harak, Y. W. Chen, Y. Nagata, and Z. Nakao. Curvelet-domain image watermarking based on edge-embedding, pages 311–317. Springer Berlin Heidelberg, Berlin, Heidelberg, 2007.
[33] F. Ji, D. Huang, and et al. Robust curvelet-domain image watermarking based on feature matching. International Journal of Computer Mathematics, 88(18):39313941, 2011.
[34] J. Xu, H. Pang, and J. Zhao. Digital image watermarking algorithm based on fast curvelet transform. Journal of Software Engineering and Applications, 2010.
[35] N. R. Brinta and P. R. Bipin. A contourlet domain watermarking algorithm. International Journal of Image Processing and Vision Sciences (IJIPVS), 2012.
[36] S. Masaebi and A. M. E. Moghaddam. A new approach for image hiding based on contourlet transform. International Journal of Electrical and Computer Engineering (IJECE), 2(5):699–708, October 2012.
[37] K. N. Mahesh, T. Manikandan, and G. V. Saptha. Non-blind image watermarking using contourlet transform. Indian Journal of Computer Science and Engineering (IJCSE), 2(1):31–38, 2011.
[38] C. Qin and X. Wen. A novel digital watermarking algorithm in contourlet domain. Journal of information & computational science, 11(2):519, 2014.
[39] S. A. Hosseini and S. Ghofrani. Digital watermarking based on contourlet-svd. Majlesi Journal of Electrical Engineering, 8(1), 2013.
[40] Y. Anusha and K. Veeraswamy. An improved contourlet transform technique for image watermarking. International Journal of Research in Computer and Communication Technology, 22(11):1128–1132, 2013.
[41] H. Bi, X. Li, and Y. Zhang. A novel hvs-based watermarking scheme in contourlet transform domain. Indonesian Journal of Electrical Engineering and Computer Science, 11(12):7516 7524, 2013.
[42] H. Sadreazami, M. O. Ahmad, and M. N. S. Swamy. A study of multiplicative watermark detection in the contourlet domain using alpha-stable distributions. IEEE Transactions on Image Processing, 23(10):4348–4360, Oct 2014.
[43] Z.-W. Shen and F.-C. Liao. Adaptive watermark algorithm based fast curvelet transform. In Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition, Hong Kong, 2008.
[44] E. Candes, L. Demanet, D. Donoho, and L. Ying. Fast discrete curvelet transforms. Multiscale Modeling & Simulation, 5(3):861–899, 2006.
[45] E. J. Candes and D. L. Donoho. Curvelets and curvilinear integrals, 2000. 10 JOURNAL OF SCIENCE AND TECHNOLOGY: ISSUE ON INFORMATION AND COMMUNICATIONS TECHNOLOGY, VOL. 3, NO. 2, DECEMBER 2017
[46] E. J. Candes and D. L. Donoho. New tight frames of curvelets and optimal representations of objects with piecewise c2 singularities. Communications on Pure and Applied Mathematics, 57(2):219–266, 2004.
[47] T. Le-Tien, K. Le-Cao, and C. Bui-Thu. An improvement of curvelet based super-resolution image processing implemented on arm at91sam9rl. In 2013 International Conference on Advanced Technologies for Communications (ATC 2013), pages 380–385, Oct 2013.
[48] D. D. Y. Po and M. N. Do. Directional multiscale modeling of images using the contourlet transform. IEEE Transactions on Image Processing, 15(6):1610–1620, June 2006.
[49] Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. Image quality assessment: From error visibility to structural similarity. IEEE Transactios on Image Processing, 13(14):600–612, 2004.
Published
2017-12-31
How to Cite
SY, Nguyen Chi; KHA, Ha Hoang; HOANG, Nguyen Minh.
An Efficient Digital Watermarking Technique for Color Images Using Directional Transforms.
Journal of Science and Technology: Issue on Information and Communications Technology, [S.l.], v. 3, n. 2, p. 1-10, dec. 2017.
ISSN 1859-1531.
Available at: <http://ict.jst.udn.vn/index.php/jst/article/view/57>. Date accessed: 21 nov. 2024.
doi: https://doi.org/10.31130/jst.2017.57.
Section
Articles
