Analysis of Impact of Lossy Audio Compression on the Robustness of Watermark Embedded in the DWT Domain for Non-blind Copyright Protection

  • Piotr Czyżyk
  • Janusz Cichowski
  • Andrzej Czyżewski
  • Bożena Kostek
Part of the Communications in Computer and Information Science book series (CCIS, volume 287)

Abstract

A methodology of non-blind watermarking of the audio content is proposed. The outline of audio copyright problem and motivation for practical applications are discussed. The algorithmic theory pertaining watermarking techniques is briefly introduced. The system architecture together with employed workflows for embedding and extracting the watermarks are described. The implemented approach is described and obtained results are reported. The possible attacks on the embedded watermark are described and the procedure of simulating the attacks is explained. The research is focused on the influence of lossy compression on the embedded watermark degradation. The peak signal to noise ratio and bit error rate are analyzed and compared. Advantages and disadvantages of the proposed approach are discussed. Future work and some possible improvements to the introduced methodology are explained.

Keywords

non-blind audio watermarking discrete wavelet transform 

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References

  1. 1.
    Al-Haj, A.M.: Advanced Techniques in Multimedia Watermarking: Image, Video and Audio Applications, New York (2010)Google Scholar
  2. 2.
    Al-Haj, A., Mohammad, A.: Digital Audio Watermarking Based on the Discrete Wavelets Transform and Singular Value Decomposition. European Journal of Scientific Research 39(1), 6–21 (2010)Google Scholar
  3. 3.
  4. 4.
    Lei, B.Y., Soon, I.Y., Li, Z.: Blind and Robust Audio Watermarking Scheme Based on SVD–DCT. Signal Processing 91(8), 1973–1984 (2011)MATHCrossRefGoogle Scholar
  5. 5.
    Bhat, K.V., Sengupta, I., Das, A.: A New Audio Watermarking Scheme Based on Singular Value Decomposition and Quantization. Multimedia Tools and Applications 52(2-3), 369–383 (2011)CrossRefGoogle Scholar
  6. 6.
    Bloom, J.A., Cox, I.J., Fridrich, J., Kalker, T., Miller, M.L.: Digital Watermarking and Steganography, Boston (2008)Google Scholar
  7. 7.
    Ciarkowski, A., Czyżewski, A.: Performance of Watermarking-Based DTD Algorithm under Time-Varying Echo Path Conditions. Intelligent Interactive Multimedia Systems and Services 6, 69–78 (2010)CrossRefGoogle Scholar
  8. 8.
    Czyżewski, A., Kostek, B., Kupryjanow, A.: Automatic Sound Restoration System - Concepts and Design. In: International Conference on Signal Processing and Multimedia Applications, pp. 1–5 (July 2011)Google Scholar
  9. 9.
    Dutta, M.K., Gupta, P., Pathak, V.K.: Perceptible Audio Watermarking for Digital Rights Management Control. In: 7th International Conference on Information, Communications and Signal Processing, vol. 1, pp. 55–59 (2009)Google Scholar
  10. 10.
    Furht, B., Kirovski, D.: Multimedia Encryption and Authentication Techniques and Applications, Florida (2006)Google Scholar
  11. 11.
    Lalitha, N.V., Suresh, G., Sailaja, V.: Improved Audio Watermarking Using DWT-SVD. International Journal of Scientific and Engineering Research 2(6), 1–7 (2011)Google Scholar
  12. 12.
    Lang, A., Dittmann, J., Spring, R., Vielhauer, C.: Audio Watermark Attacks: from single to profile attacks. In: Proceedings of the 7th Workshop on Multimedia and Security, New York (2005)Google Scholar
  13. 13.
    Maha, C., Maher, E., Chokri, B.A.: A blind audio watermarking scheme based on Neural Network and Psychoacoustic Model with Error correcting code in Wavelet Domain. In: 3rd Int. Symp. on Communications, Control and Signal Processing, pp. 1138–1143 (2008)Google Scholar
  14. 14.
    Petitcolas, F.A.P., Anderson, R.J., Kuhn, M.G.: Attacks on Copyright Marking Systems. In: Aucsmith, D. (ed.) IH 1998. LNCS, vol. 1525, pp. 218–238. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  15. 15.
    RFC 20: ASCII format for Network Interchange, ANSI X3.4 (October 1969)Google Scholar
  16. 16.
    Vongpraphip, S., Ketcham, M.: An Intelligence Audio Watermarking Based on DWT- SVD Using ATS. In: Global Congress on Intelligent Systems, GCIS 2009, pp. 150–154 (May 2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Piotr Czyżyk
    • 1
  • Janusz Cichowski
    • 1
  • Andrzej Czyżewski
    • 1
  • Bożena Kostek
    • 1
  1. 1.Multimedia Systems DepartmentGdansk University of TechnologyGdanskPoland

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