Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
권호 표지

Similar Patterns for Semi-blind Watermarking

  • Cho, Jae-Hyun (School of Computer & Information Engineering, Catholic University)
  • Published : 2004.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we present a watermarking scheme based on the DWT (Discrete Wavelet Transform) and the ANN (Artificial Neural Network) to ensure the copyright protection of the digital images. The problem to embed watermark is not clear to select important coefficient in the watermarking. We used the RBF (Radial-Basis Function) to solve the problem. We didn't apply the whole wavelet coefficients, but applied to only the wavelet coefficients in the selected node. Using the ANN, although even the watermark casting process and watermark verification process are in public, nobody knows the location of embedding watermark except of authorized user. As the result, the watermark is good at the strength test-filtering, geometric transform and etc.

Keywords

References

  1. M. D. Swanson, M. Kobayashi, and A. TewFik, 'Multimedia Data-Embedding and Watermarking Technologies,' In Proceeding of IEEE, Vol. 86, No. 6, June 1998
  2. I. Pitas and T. Kaskalis, 'Applying Signatures on Digital Images,' In Proceeding of IEEE Nonlear Signal Processing Workshop, Thessaloniki, Greece, 1995
  3. C. F. Osborne, R. G. Schyndel and A. Z. Tirkel, 'A Digital Watermarking' International Conference on Image Processing, November 1994
  4. I. J. Cox, J. Kilian, T. Leighton and T. Shamoon, 'Secure Spread Spectrum Watermarking for Multimedia'" IEEE Transaction on Image Processing, Vol. 6, No. 12, pp. 1673-1687, 1997 https://doi.org/10.1109/83.650120
  5. I. J. Cox, M. L. Miller and J. A. Bloom, Digital Watermarking, Academic Press, 2002
  6. M. Kutter, F. Jordan, and F. Bossen, 'Digital Signature of Color images using Amplitude Modulation,' In Ishwar K. Sethi, editor, Proceedings of the SPIE Conference on Storage and Retrieval for Image and Video Databases, Vol. 2952, pp. 518 - 526, San Jose, USA,1997
  7. D. Kundur and D. Hatzinakos, 'Digital watermarking using Multiresolution Wavelet Decomposition,' In Proceeding of IEEE ICASSP '98, Vol. 5, pp. 2969 - 2972, Seattle, WA, USA, May 1998
  8. H. J. Wang, P. C. Su and C. J. Kuo,'"Wavelet-based digital image watermarking'" Optics Express 3, pp. 497, December 1998
  9. X. G. Xia, C. G. Boncelet and G. R. Arce, 'Wavelet Transform based Watermark for Digital Images,' Optics Express 3, pp. 497, December 1998
  10. S. Mallat', 'Multi-Frequency Channel Decom-position of Images Wavelets Models,' IEEE Trans. on Information Theory, Vol. 11, No.7, July 1992
  11. S. Haykin, Neural Networks: A Comprehensive Foundation, MacMillan, 1994
  12. J. M. Shapiro, 'Embedded Image coding using zerotreesof wavelet coefficients,' IEEE Transaction on Signal Processing, Vol. 41, No. 12, pp. 3445-3462, December 1993 https://doi.org/10.1109/78.258085
  13. M. Kutter, 'http://www.watermarkingworld.org/,'WatermarkingWorld, 2000
  14. T. Kohonen, 'Self-Grganizing Maps,' Berlin: Springer Verlag. First edition was 1995, second edition 1997
  15. K. I. Diamantaras, and S. Y. Kung, Principal Component Neural Networks, Theory and Applications, NY. Wiley, 1996
  16. R. C. Gonzalez, R. E. Woods, Digital image processing, Second edition, Prentice Hall, 2001
  17. Darpa, Neural Network Study, AFCEA International Press. 1988