Robust  Watermarking Using <i>n</i>-Diagonalization Based on Householder    Transform

Jaesung Park; Kazuhito Sawase; Hajime Nobuhara

doi:10.20965/jaciii.2014.p0549

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JACIII Vol.18 No.4 pp. 549-557

doi: 10.20965/jaciii.2014.p0549

(2014)

Paper:

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Robust Watermarking Using n-Diagonalization Based on Householder Transform

Jaesung Park, Kazuhito Sawase, and Hajime Nobuhara

Department of Intelligent Interaction Technologies, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

Received:

October 31, 2013

Accepted:

May 1, 2014

Published:

July 20, 2014

Keywords:

n-diagonalzation, discrete wavelet transform, householder transform

Abstract

Digital image watermarking based on singular value decomposition (SVD) is highly robust against misuse, but lacks the ability to distinguish whether watermarks are correct due to the importance of singular values being lower than two orthogonal matrices. To achieve highly accurate watermark extraction while maintaining high robustness, we propose robust watermarking based on discrete wavelet transform (DWT) and n-diagonalization formalized by Householder transformation. We propose that DWT be used to ensure visibility and that n-diagonalization be used to control information quantity related to watermark extraction accuracy. Experimental results confirm the robustness of our proposed method and that the extraction accuracy of the proposed method is approximately 2 times better than that of SVD.

Cite this article as:

J. Park, K. Sawase, and H. Nobuhara, “Robust Watermarking Using n-Diagonalization Based on Householder Transform,” J. Adv. Comput. Intell. Intell. Inform., Vol.18 No.4, pp. 549-557, 2014.

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References

[1] Z. Lei, “A Improve Robust Watermarking Algorithm for Binary Images,” Advanced Materials Research, Vols.756-759, pp. 3775-3780, 2013.
[2] E. P. Remya,M. G. Sumithra, “Development Of A NewWatermarking Algorithm For Telemedicine Applications,” Int. J. of Engineering Research and Applications, Vol.3, No.1, pp. 962-968, 2013.
[3] P. Tao and A. M. Eskicioglu, “A robust multiple watermarking scheme in the Discrete Wavelet Transform domain,” Internet Multimedia Management Systems V, Proc. of the SPIE, Vol.5601, pp. 133-144, 2004.
[4] G. Bhatnagar and B. Raman, “A new robust reference watermarking scheme based on DWT-SVD,” J. of Computer Standards and Interfaces 31, Vol.31, No.5, pp. 1002-1013, 2009.
[5] M. J. Shensa, “The Discrete Wavelet Transform: Wedding the A Trous and Mallat Algorithms,” IEEE Trans. on Signal Processing, Vol.40, No.10, pp. 2464-2482, 1992.
[6] V. Gorodetski, L. Popyack, V. Samoilov, and V. Skormin, “SVDbased Approach to Transparent Embedding Data into Digital Images,” Information Assurance in Computer Networks, Lecture Notes in Computer Science, Vol.2052, pp. 263-274, 2001.
[7] G. H. Golub and C. Reinsch, “Singular value decomposition and least squares solutions,” Numerische Mathematik, Vol.14, No.5, pp. 403-420, 1970.
[8] M. Barni, F. Bartolini, and A. Piva, “Improved Wavelet-Based Watermarking Through Pixel-Wise Masking,” IEEE Trans. on Image Processing, Vol.10, No.5, pp. 783-791, 2001.
[9] K.-L. Chung and W.-M. Yan, “The Complex Householder Transform,” IEEE Trans. on Signal Processing, Vol.45, No.9, pp. 2374-2376, 1997.
[10] N. Bosner, “Accuracy and efficiency of one-sided bidiagonalization algorithm,” Third Croatian Congress of Mathematics, Jun. 16-18, 2004.
[11] The USC-SIPI Image Database,
“http://sipi.usc.edu/database/database.php”
[Accessed October 16, 2013]
[12] Dataset of standard 512×512 grayscale test images,
“http://decsai.ugr.es/cvg/CG/base.htm”
[Accessed October 16, 2013]

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] Z. Lei, “A Improve Robust Watermarking Algorithm for Binary Images,” Advanced Materials Research, Vols.756-759, pp. 3775-3780, 2013.

[2] [2] E. P. Remya,M. G. Sumithra, “Development Of A NewWatermarking Algorithm For Telemedicine Applications,” Int. J. of Engineering Research and Applications, Vol.3, No.1, pp. 962-968, 2013.

[3] [3] P. Tao and A. M. Eskicioglu, “A robust multiple watermarking scheme in the Discrete Wavelet Transform domain,” Internet Multimedia Management Systems V, Proc. of the SPIE, Vol.5601, pp. 133-144, 2004.

[4] [4] G. Bhatnagar and B. Raman, “A new robust reference watermarking scheme based on DWT-SVD,” J. of Computer Standards and Interfaces 31, Vol.31, No.5, pp. 1002-1013, 2009.

[5] [5] M. J. Shensa, “The Discrete Wavelet Transform: Wedding the A Trous and Mallat Algorithms,” IEEE Trans. on Signal Processing, Vol.40, No.10, pp. 2464-2482, 1992.

[6] [6] V. Gorodetski, L. Popyack, V. Samoilov, and V. Skormin, “SVDbased Approach to Transparent Embedding Data into Digital Images,” Information Assurance in Computer Networks, Lecture Notes in Computer Science, Vol.2052, pp. 263-274, 2001.

[7] [7] G. H. Golub and C. Reinsch, “Singular value decomposition and least squares solutions,” Numerische Mathematik, Vol.14, No.5, pp. 403-420, 1970.

[8] [8] M. Barni, F. Bartolini, and A. Piva, “Improved Wavelet-Based Watermarking Through Pixel-Wise Masking,” IEEE Trans. on Image Processing, Vol.10, No.5, pp. 783-791, 2001.

[9] [9] K.-L. Chung and W.-M. Yan, “The Complex Householder Transform,” IEEE Trans. on Signal Processing, Vol.45, No.9, pp. 2374-2376, 1997.

[10] [10] N. Bosner, “Accuracy and efficiency of one-sided bidiagonalization algorithm,” Third Croatian Congress of Mathematics, Jun. 16-18, 2004.

[11] [11] The USC-SIPI Image Database,
“http://sipi.usc.edu/database/database.php”
[Accessed October 16, 2013]

[12] [12] Dataset of standard 512×512 grayscale test images,
“http://decsai.ugr.es/cvg/CG/base.htm”
[Accessed October 16, 2013]