Skip to main content

Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection

Abstract

We propose a novel approach to detect the watermark message embedded in images under the form of a linear frequency modulated chirp. Localization of several time-frequency distributions (TFDs) is studied for different frequency modulated signals under various noise conditions. Smoothed pseudo-Wigner-Ville distribution (SPWVD) is chosen and applied to detect and recover the corrupted image watermark bits at the receiver. The synthesized watermark message is compared with the referenced one at the transmitter as a detection evaluation scheme. The correlation coefficient between the synthesized and the referenced chirps reaches 0.9 or above for a maximum bit error rate of 15% under intentional and nonintentional attacks. The method provides satisfactory result for detection of image watermark messages modulated as chirp signal and could be a potential tool in multimedia security applications.

References

  1. 1.

    Ramalingam A, Krishnan S: A novel robust image watermarking using a chirp based technique. Proceedings of the Canadian Conference on Electrical and Computer Engineering, May 2004, Niagara Falls, Ontario, Canada 4: 1889–1892.

    Google Scholar 

  2. 2.

    Erkucuk S, Krishnan S, Zeytinoglu M: Robust audio watermarking using a chirp based technique. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME '03), July 2003, Baltimore, Md, USA 2: 513–516.

    Google Scholar 

  3. 3.

    Kay S, Boudreaux-Bartels G: On the optimality of the Wigner distribution for detection. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '85), April 1985, Tampa, Fla, USA 10: 1017–1020.

    Article  Google Scholar 

  4. 4.

    Dhanoa JS, Hughes EJ, Ormondroyd RF: Simultaneous detection and parameter estimation of multiple linear chirps. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '03), April 2003, Hong Kong 6: 129–132.

    Google Scholar 

  5. 5.

    Torres J, Cabiscol P, Grau J: Radar chirp detection through wavelet transform. Proceedings of the 5th Biannual World Automation Congress, June 2002, Orlando, Fla, USA 13: 227–232.

    Article  Google Scholar 

  6. 6.

    Rangayyan RM, Krishnan S: Feature identification in the time-frequency plane by using the Hough-Radon transform. Pattern Recognition 2001, 34(6):1147–1158. 10.1016/S0031-3203(00)00073-X

    Article  Google Scholar 

  7. 7.

    Sun Y, Willett P: Hough transform for long chirp detection. IEEE Transactions on Aerospace and Electronic Systems 2002, 38(2):553–569. 10.1109/TAES.2002.1008986

    Article  Google Scholar 

  8. 8.

    Carlson BD, Evans ED, Wilson SL: Search radar detection and track with the Hough transform. I: system concept. IEEE Transactions on Aerospace and Electronic Systems 1994, 30(1):102–108. 10.1109/7.250410

    Article  Google Scholar 

  9. 9.

    Boudreaux-Bartels GF, Parks T: Time-varying filtering and signal estimation using Wigner distribution synthesis techniques. IEEE Transactions on Acoustics, Speech, and Signal Processing 1986, 34(3):442–451. 10.1109/TASSP.1986.1164833

    MathSciNet  Article  Google Scholar 

  10. 10.

    Krattenthaler W, Hlawatsch F: Time-frequency design and processing of signals via smoothed Wigner distributions. IEEE Transactions on Signal Processing 1993, 41(1):278–287. 10.1109/TSP.1993.193145

    Article  Google Scholar 

  11. 11.

    Francos A, Porat M: Analysis and synthesis of multicomponent signals using positive time-frequency distributions. IEEE Transactions on Signal Processing 1999, 47(2):493–504. 10.1109/78.740132

    Article  Google Scholar 

  12. 12.

    Peleg S, Friedlander B: Multicomponent signal analysis using the polynomial-phase transform. IEEE Transactions on Aerospace and Electronic Systems 1996, 32(1):378–387.

    Article  Google Scholar 

  13. 13.

    Peleg S, Friedlander B: The discrete polynomial-phase transform. IEEE Transactions on Signal Processing 1995, 43(8):1901–1914. 10.1109/78.403349

    Article  Google Scholar 

  14. 14.

    Lee S-J, Jung S-H: A survey of watermarking techniques applied to multimedia. Proceedings of the IEEE International Symposium on Industrial Electronics (ISIE '01), June 2001, Pusan, South Korea 1: 272–277.

    Google Scholar 

  15. 15.

    Mobasseri BG: Digital watermarking in joint time-frequency domain. Proceedings of the International Conference on Image Processing (ICIP '02), September 2002, Rochester, NY, USA 3: 481–484.

    Google Scholar 

  16. 16.

    Sattar F, Barkat B: A new time-frequency based private fragile watermarking scheme for image authentication. Proceedings of the 7th International Symposium on Signal Processing and Its Applications (ISSPA '03), July 2003, Paris, France 2: 363–366.

    Google Scholar 

  17. 17.

    Bender W, Gruhl D, Morimoto N, Lu A: Techniques for data hiding. IBM Systems Journal 1996, 35(3–4):313–336.

    Article  Google Scholar 

  18. 18.

    Podilchuk CI, Zeng W: Image-adaptive watermarking using visual models. IEEE Journal on Selected Areas in Communications 1998, 16(4):525–539. 10.1109/49.668975

    Article  Google Scholar 

  19. 19.

    Krishnan S: Instantaneous mean frequency estimation using adaptive time-frequency distributions. Proceedings of the Canadian Conference on Electrical and Computer Engineering, May 2001, Toronto, Ontario, Canada 1: 141–146.

    Google Scholar 

  20. 20.

    Mallat SG, Zhang Z: Matching pursuits with time-frequency dictionaries. IEEE Transactions on Signal Processing 1993, 41(12):3397-3415. 10.1109/78.258082

    Article  Google Scholar 

  21. 21.

    Hlawatsch F, Boudreaux-Bartels GF: Linear and quadratic time-frequency signal representations. IEEE Signal Processing Magazine 1992, 9(2):21–67. 10.1109/79.127284

    Article  Google Scholar 

  22. 22.

    Hlawatsch F, Manickam TG, Urbanke RL, Jones W: Smoothed pseudo-Wigner distribution, Choi-Williams distribution, and cone-kernel representation: ambiguity-domain analysis and experimental comparison. Signal Processing 1995, 43(2):149–168. 10.1016/0165-1684(94)00150-X

    Article  Google Scholar 

  23. 23.

    Pereira S, Voloshynovskiy S, Madueno M, Marchand-Maillet S, Pun T: Second generation benchmarking and application oriented evaluation. Proceedings of the Information Hiding Workshop III, April 2001, Pittsburgh, Pa, USA

    Google Scholar 

  24. 24.

    Xia X, Boncelet CG, Arce GR: A multiresolution watermark for digital images. Proceedings of the IEEE International Conference on Image Processing, October 1997, Santa Barbara, Calif, USA 1: 548–551.

    Article  Google Scholar 

  25. 25.

    Cox I, Leighton F, Shamoon T: Secure spread spectrum watermarking for multimedia. IEEE Transactions on Image Processing 1997, 6(12):1673–1687. 10.1109/83.650120

    Article  Google Scholar 

  26. 26.

    Pereira S, Voloshynovskiy S, Pun T: Optimal transform domain watermark embedding via linear programming. Signal Processing 2001, 81(6):1251–1260. special issue: information theoretic issues in digital watermarking 10.1016/S0165-1684(01)00042-1

    Article  Google Scholar 

  27. 27.

    Peyrin F, Prost R: A unified definition for the discrete-time, discrete-frequency, and discrete-time/frequency Wigner distributions. IEEE Transactions on Acoustics, Speech, and Signal Processing 1986, 34(4):858–867. 10.1109/TASSP.1986.1164880

    Article  Google Scholar 

  28. 28.

    Pavel S, Akl SG: Efficient algorithms for the Hough transform on arrays with reconfigurable optical buses. Proceedings of 10th International Parallel Processing Symposium (IPPS '96), April 1996, Honolulu, Hawaii, USA 697–701.

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Lam Le.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Le, L., Krishnan, S. Time-Frequency Signal Synthesis and Its Application in Multimedia Watermark Detection. EURASIP J. Adv. Signal Process. 2006, 086712 (2006). https://doi.org/10.1155/ASP/2006/86712

Download citation

Keywords

  • Error Rate
  • Information Technology
  • Detection Evaluation
  • Satisfactory Result
  • Quantum Information