IC3 2010: Contemporary Computing pp 107-118 | Cite as

A New SVD Based Watermarking Framework in Fractional Fourier Domain

  • Gaurav Bhatnagar
  • Balasubramanian Raman
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 94)

Abstract

In this paper, a new robust watermarking scheme is proposed using fractional Fourier transform (FrFT) and singular value decomposition. The core idea of the proposed scheme is to decompose an image using FrFT followed by the non-overlapping block segmentation. A new key matrix is then formed by taking maximum singular values of all non-overlapping blocks. For embedding this key matrix is used and is done by modifying singular values with the singular values of the watermark. The experimental results show better visual imperceptibility and resiliency of the proposed scheme against intentional or un-intentional variety of attacks.

Keywords

Singular Value Decomposition Watermark Image Watermark Scheme JPEG Compression Digital Watermark 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Cox, I.J., Miller, M.L., Bloom, J.A.: Digital watermarking. Morgan Kaufmann, San Francisco (2001)Google Scholar
  2. 2.
    Kim, W.G., Lee, J.C., Lee, W.D.: An image watermarking scheme with hidden signatures. In: IEEE International Conference on Image Processing, Kobe, Japan, vol. 2, pp. 206–210 (1999)Google Scholar
  3. 3.
    Voyatzis, G., Pitas, I.: Chaotic watermarks for embedding in the spatial digital image domain. In: IEEE International Conference on Image Processing, Chicago, Illinois, USA, vol. 2, pp. 432–435 (1998)Google Scholar
  4. 4.
    Xia, X., Boncelet, C.G., Arce, G.R.: A multiresolution watermark for digital images. In: IEEE International Conference on Image Processing, Santa Barbara, CA, vol. 3, pp. 548–551 (1997)Google Scholar
  5. 5.
    Kundur, D., Hatzinakos, D.: Towards robust logo watermarking using meltiresolution image fusion. IEEE Transcations on Multimedia 6, 185–197 (2004)CrossRefGoogle Scholar
  6. 6.
    Dawei, Z., Guanrong, C., Wenbo, L.: A chaos-based robust wavelet-domain watermarking algorithm. J. Chaos Solitons Fractals 22, 47–54 (2004)MATHCrossRefGoogle Scholar
  7. 7.
    Djurovic, I., Stankovic, S., Pitas, I.: Digital watermarking in the fractional fourier transformation domain. Journal of Network and Computer Applications 24(4), 167–173 (2001)CrossRefGoogle Scholar
  8. 8.
    Liu, R., Tan, T.: An SVD-Based Watermarking Scheme for Protecting Rightful Ownership. IEEE Transactions on Multimedia 4(1), 121–128 (2002)CrossRefGoogle Scholar
  9. 9.
    Chandra, D.V.S.: Digital Image Watermarking Using Singular Value Decomposition. In: IEEE Midwest Symposium on Circuits and Systems, Tulsa, Oklahoma, pp. 264–267 (2002)Google Scholar
  10. 10.
    Ganic, E., Eskicioglu, A.M.: Robust Embedding of Visual Watermarks Using DWT-SVD. Journal of Electronic Imaging (2005)Google Scholar
  11. 11.
    Sverldov, A., Dexter, S., Eskicioglu, A.M.: Robust DCT-SVD Domain Image Watermarking for Copyright Protection: Embedding Data in All Frequencies. In: European Signal Processing Conference, Antalya, Turkey, pp. 1–4 (2005)Google Scholar
  12. 12.
    Li, Q., Yuan, C., Zong, Y.Z.: Adaptive DWT-SVD Domain Image Watermarking Using Human Visual Model. In: International Conference on Advanced Communication Technology, Phoenix Park, Korea, pp. 1947–1951 (2007)Google Scholar
  13. 13.
    Lin, C.H., Jen, J.S., Kuo, L.C.: Distributed discrete wavelet transformation for copyright protection. In: Intrnational Workshop on Image Analysis for Multimedia Interactive Services, Incheon, Korea, pp. 53–56 (2006)Google Scholar
  14. 14.
    Qi, X., Brimley, B., Brimley, G.: An adaptive QIM- and SVD-based digital image watermarking scheme in the wavelet domain. In: International Conference on Image Processing, San Diego, California, USA, pp. 421–424 (2008)Google Scholar
  15. 15.
    Namias, V.: The fractional order Fourier transform and its application to quantum mechanics. J. Inst. Math. Appl. 25, 241–265 (1980)MATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Strang, G.: Introduction to Linear Algebra. Wellesley-Cambridge Press (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gaurav Bhatnagar
    • 1
  • Balasubramanian Raman
    • 2
  1. 1.University of WindsorWindsorCanada
  2. 2.Indian Institute of Technology RoorkeeRoorkeeIndia

Personalised recommendations