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Sign Correlation Detector for Blind Image Watermarking in the DCT Domain

  • Xiaochen Bo
  • Lincheng Shen
  • Wensen Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2195)

Abstract

Digital watermarking is a key technique for protecting intellectual property of digital media. Due to the ability to detect watermark without the original image, blind watermarking is very useful if there are too many images to be authenticated. In this paper, we pose the difference on mathematical models between private watermark detection and blind watermark detection, and then point out the limitation of linear correlation detector (LCD). After reviewing some statistical models which have been proposed to better characterize the DCT coefficients of images, we deduce a new blind watermark detector — sign correlation detector (SCD) based on the Laplacian distribution model. Computing result of asymptotic relative efficiency demonstrates the effectiveness of the detector. A series of experiments show its robustness.

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References

  1. 1.
    Cox, I.J., Kilian, J., Leighton, T., Shamoon, T.: Secure Spread Spectrum Watermarking for Multimedia. IEEE Trans. on Image Processing. 6 (1997) 1673–1687CrossRefGoogle Scholar
  2. 2.
    Barni, M., Bartolini, F., Cappellini, V., Piva, A.: A DCT-Domain System for Robust Image Watermarking. Signal Processing. 3 (1998) 357–372CrossRefGoogle Scholar
  3. 3.
    M. Barni, F. Bartolini, V. Cappellini, A. Piva: “Statistical Modeling of Full Frame DCT Coefficients ”. Proceedings of EUSIPCO '98, Rhodes, Greece, 1998.Google Scholar
  4. 4.
    Reininger, R.C., Gibson, J. D.: Distributions of the two-dimensional DCT Coefficients for Images. IEEE Trans. on Communications, 6 (1983) 835–839CrossRefGoogle Scholar
  5. 5.
    Joshi, R. J., Fischer, T. R.: Comparison of Generalized Gaussian and Laplacian Modeling in DCT Image Coding. IEEE Signal Processing Letters, 5(1995) 81–82CrossRefGoogle Scholar
  6. 6.
    Craver, S., Memon, N., Yeo, B., Yeung, M.: Resolving Rightful Ownerships with Invisible Watermarking Techniques: Limitations, Attacks, and Implication, IEEE Journal on Selected Areas in Comm., 4 (1998) 573–586CrossRefGoogle Scholar
  7. 7.
    Lam, E.Y., Goodman, J.W.: A Mathematical Analysis of the DCT Coefficients Distributions for Images, IEEE Trans. on Image Processing, 10 (2000) 1661–1666CrossRefGoogle Scholar
  8. 8.
    Chen, B. H., Random Signal Processing, Publishing House of National Defense Industry, Beijing (1996)Google Scholar
  9. 9.
    Feng, Y. M., Shao, Y. M., Zhang, X.: Digital Image Compression and Coding, Chinese Publishing House of Railway, Beijing (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Xiaochen Bo
    • 1
  • Lincheng Shen
    • 1
  • Wensen Chang
    • 1
  1. 1.Institute of AutomationNational University of Defense TechnologyChangshaP.R.CHINA

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