• DocumentCode
    2632383
  • Title

    Watermarking Via Bspline Expansion and Natural Preserving Transforms

  • Author

    Fahmy, M.F. ; Raheem, G.M.A. ; Mohammed, O.S. ; Fahmy, O.M. ; Fahmy, G.F.

  • Author_Institution
    Dept. of Electr. Eng., Assiut Univ., Asyut
  • fYear
    2008
  • fDate
    16-19 Dec. 2008
  • Firstpage
    336
  • Lastpage
    341
  • Abstract
    In this paper, two approaches are proposed for digital image watermarking. In the first approach, we rely on embedding all the watermarking information in the approximation coefficients of the host´s image wavelet decomposition. This is achieved by combining a weighted least squares Bspline coefficient expansion of the watermarking image, to the host´s approximation coefficients. In order to make the size of Bspline expansion less or equal to the size of the host´s approximation matrix, the watermarking image has to be decimated. The second approach relies on applying natural preserving transforms NPT, in a symmetrical manner to the host´s image. In this case, the logo or the secret key replaces some of the host´s image bottom lines. After applying NPT, the original host image bottom lines, replace the watermarked ones to make the host image looks natural. A novel fast least squares algorithm is proposed for watermark extraction. Illustrative examples are given, to show the effectiveness of these methods. Thes results show that the proposed Bspline data hiding technique is robust to compression, as well as the abilities of watermark extraction of any NPT watermarked images.
  • Keywords
    data encapsulation; image coding; least squares approximations; splines (mathematics); transforms; watermarking; wavelet transforms; Bspline data hiding technique; approximation coefficients; approximation matrix; digital image watermarking; image wavelet decomposition; natural preserving transforms; watermark extraction; watermarking information; weighted least squares Bspline coefficient expansion; Data encapsulation; Data mining; Digital images; Image coding; Least squares approximation; Least squares methods; Matrix decomposition; Robustness; Symmetric matrices; Watermarking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Information Technology, 2008. ISSPIT 2008. IEEE International Symposium on
  • Conference_Location
    Sarajevo
  • Print_ISBN
    978-1-4244-3554-8
  • Electronic_ISBN
    978-1-4244-3555-5
  • Type

    conf

  • DOI
    10.1109/ISSPIT.2008.4775687
  • Filename
    4775687