Robust image watermarking based on QR factorization and LWT

  • Authors

    • Areej M. Abduldaim University of Technology
    • Mohammed Qasim Hamid University of Technology
    2019-03-28
    https://doi.org/10.14419/ijet.v7i4.23661
  • Imperceptibility, Lifting Wavelet Transform (LWT), QR Matrix Factorization, Robustness, Watermarking.

  • Abstract

    Personal information needs to be safely transmitted over the internet and addressed effectively. Robust watermarking of biometric patterns is a convenient technique used to increase security and data authentication, which is decisive due to the uniqueness of some types of watermark images. Biometrics like fingerprints, voice, retina, iris, and blood vessel tree are being increasingly utilized for affirmative identification since they cannot be mislaid or forgotten and represent perceptible components. Furthermore, from the viewpoint of linear algebra, any digital image can be expressed by a matrix consists of a non-negative number of scalars. The objective of this paper is to intro-duce a newfangled blind watermarking algorithm using matrix decomposition method named QR. The application and analysis of the QR Matrix decomposition technique illustrate its impact on each block of the LH2 subband in the frequency domain that represents the output of two-level LWT (Lifting Wavelet Transform). The experimental results display that the newly proposed mechanism is secure and imperceptible. The final conclusion shows that the proposed method can get better PSNRs and that the proposed algorithm fulfills better watermark imperceptibility and robustness beneath different attacks.

     

     

     


  • References

    1. [1] Guru. J and Damecha. H,†Digital Watermarking Classification : A Surveyâ€, International Journal of Computer Science Trends and Technology (IJCST), Vol.2, No.5, (2014), available online:http://www.ijcstjournal.org/volume-2/issue-5/IJCST-V2I5P2.pdf.

      [2] Thajeel. S.A, Kadhim. L.M and Abdlateef. S.A †A new color image watermarking technique using multiple decompositions,â€, Journal Of Theoretical And Applied Information Technology, Vol.95, No.10, (2017), pp.2323-2331, available online: http://www.jatit.org/volumes/Vol95No10/24Vol95No10.pdf.

      [3] Su. Q, Wang. G, Zhang. X, Lv. G and Chen. B,†A new algorithm of blind color image watermarking based on LU decompositionâ€, Multidim Syst Sign Process, Vol.29, No.3, (2018), pp.1055-1047.

      [4] Wang. S, Zhao. W and Wang. Z, (2008)†A gray scale watermarking algorithm based on LU factorization", International Symposiums on Information Processing IEEE, pp.598-602. https://doi.org/10.1109/ISIP.2008.149.

      [5] Jane. O and ElbaÅŸi. E,†A new approach of nonblind watermarking methods based on DWT and SVD via LU decompositionâ€, Journal name,Vol.22, (2014), pp.1354-1366, available online: http://journals.tubitak.gov.tr/elektrik/issues/elk-14-22-5/elk-22-5-19-1212-75.pdf.

      [6] Zhang. H, Wang. C and Zhou. X,†A robust image watermarking scheme based on SVD in the spatial domainâ€, Future Internet, Vol.45, No.9, (2017), pp.1-16, available online: https://www.mdpi.com/1999-5903/9/3/45/htm.

      [7] Trefethen. L. N and Bau. D, Numerical Linear Algebra, SIAM, (1997).

      [8] Golub, Gene. H, Loan. V and Charles F, Matrix Computations (3rd ed.), Johns Hopkins, (1996).

      [9] Phadikar. A, Maity. S. P, and Kundu. M. K,†Quantization based data hiding scheme for efficient quality access control of images using DWT via lifting, Proc. Sixth Indian Conference on Computer Visionâ€, Graphics and Image Processing IEEE, Bhubaneswar, India, (2008), pp: 265- 272,

      [10] Fan. W, Chen. J, Zhen. J,†SPIHT algorithm based on fast lifting wavelet transform in image compressionâ€, International Conference on Computational and Information Science, Computational Intelligence and Security, (2005), pp: 838–844, https://doi.org/10.1007/11596981_122.

      [11] Lei. B, Soon. IY, Zhou. F, Li. Z and Lei. H,†A robust audio watermarking scheme based on lifting wavelet transform and singular value decompositionâ€, Signal Processing, Vol.92, No.9, (2012), pp. 1985–2001. https://doi.org/10.1016/j.sigpro.2011.12.021.

      [12] Zhang. S.Q, He. N, Lv. J.T, Xu. X.H and Zang. X.Y,†Research of the lifting wavelet arithmetic and applied in rotary mechanic fault diagnosisâ€, Journal of Physics: Conference Series 48, (2006), pp: 696–700, https://doi.org/10.1088/1742-6596/48/1/131.

      [13] Zheng. J, Lu. R, Sun. L, Zhuang. S,†Low-noise multiple watermarks technology based on complex double random phase encoding methodâ€, Proceedings Volume 7851, Information Optics and Optical Data Storage, (2010).

      [14] Marek. M and Schreiber. I,†Chaotic behavior of deterministic dissipativeâ€, Cambridge University Press, Cambridge, (1991), pp:XX-YY,

      [15] Mehta. R , Rajpal.N and Virendra P,†LWT- QR decomposition based robust and efficient image watermarking scheme using Lagrangian SVRâ€, Multimedia Tools and Applications, Vol.75, No.7, (2016), pp.4129.

      [16] Guo. J.M, Prasetyo. H,†False-positive-free SVD-based image watermarkingâ€, J. Vis. Commun. Image Represent, Vol.25, (2014), pp:1149-1163, https://doi.org/10.1016/j.jvcir.2014.03.012.

      [17] Jain. C, Arora. S, Panigrahi. P.K,†A reliable SVD based watermarking schemeâ€, Comput. Sci, (2008).

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  • How to Cite

    M. Abduldaim, A., & Qasim Hamid, M. (2019). Robust image watermarking based on QR factorization and LWT. International Journal of Engineering & Technology, 7(4), 5358-5362. https://doi.org/10.14419/ijet.v7i4.23661

    Received date: 2018-12-10

    Accepted date: 2019-01-16

    Published date: 2019-03-28