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Image Ownership Verification Via Unitary Transform of Conjugate Quadrature Filter

  • Jianwei Yang
  • Xinxiang Zhang
  • Wen-Sheng Chen
  • Bin Fang
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 345)

Abstract

A wavelet-based watermarking system is described for ownership verification of digital images. The wavelet filters used in this system are constructed by unitary transform of two-dimensional conjugate quadrature filter (CQF). Tensor-product wavelet filters are only special cases of this construction. This construction provides more ways to randomly generate perfect reconstruction filters, and will increase the difficulty for counterfeiters to gain the exact knowledge of our watermark. Furthermore, the watermark is inserted into several middle-frequency sub-bands and the existence of the watermark is asserted if any one of the correlation values is greater than a pre-determined threshold. Experimental results show that the proposed algorithm achieves invisibility, blind, and robustness to noising, sharpening, cropping etc.

Keywords

Unitary Transform Watermark Image Watermark Scheme JPEG Compression Wavelet Filter 
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.

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References

  1. 1.
    Barni, M., Bartolini, F., Piva, A.: Improved Wavelet-based Watermarking through Pixel-wise Masking. IEEE Trans. on Image Processing. 10 (2001) 783–791zbMATHCrossRefGoogle Scholar
  2. 2.
    Wang, Y., Doherty, J., Robert, E.: A Wavelet-based Watermarking Algorithm for Ownership Verification of Digital Image. IEEE Transactions on Image Processing, 11 (2002) 77–88CrossRefGoogle Scholar
  3. 3.
    Huang, Z., Jiang, Z.: Image Ownership Verification via Private Pattern and Watermarking Wavelet Filters. In: Proceedings of the VII Digital Image Computing: Techniques and Applications (Sydney)(2003) 801–810Google Scholar
  4. 4.
    Huang, Z., Jiang, Z.: Watermarking still Images Using Parametrized Wavelet Systems. In Proceedings of Image and Vision Computing’03 (Palmerston North) (2003) 215–220Google Scholar
  5. 5.
    Lai, M.: Construction of Multivariate Compactly Supported Orthonormal Wavelets. Advances in Computational Math. (to appear)Google Scholar
  6. 6.
    Vaidyanathan, P., Nguyen, T., Doganata, Z., Saramaki, T.: Improved Technique for Design of Perfect Reconstruction Fir qmf Banks with Lossless Polyphase Matrices. IEEE Trans. Acoust. Speech, Signal Processing, 37 (1989) 1042–1056CrossRefGoogle Scholar
  7. 7.
    Gonzalez, R., Woods R.: Digital Image Processing. Prentice Hall, 2nd edition (2001)Google Scholar
  8. 8.
    Zhao, D., Chen, G., Liu, W.: A Chaos-based Robust Wavelet-domain Watermarking Algorithm. Chaos, Solitons and Fractals, 22 (2004) 47–54zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jianwei Yang
    • 1
  • Xinxiang Zhang
    • 2
  • Wen-Sheng Chen
    • 3
    • 4
  • Bin Fang
    • 5
  1. 1.Department of MathematicsNanjing University of Information Science and TechnologyNanjingP.R. China
  2. 2.Department of Computer ScienceHenan Institute of Finance and EconomicsZhengzhouP.R. China
  3. 3.Department of MathematicsShenzhen UniversityShenzhenP.R.China
  4. 4.Key Laboratory of Mathematics MechanizationCASBeijingP.R.China
  5. 5.Department of Computer ScienceChongqing UniversityChongqingP.R. China

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