Multimedia Tools and Applications

, Volume 76, Issue 3, pp 3783–3807 | Cite as

Robust covert communication using high capacity watermarking



Generally, in watermarking techniques the size of the watermark is very small when compared to the host image. In other words, a little amount of watermark is embedded in the huge quantity of image pixels as the notice of legitimate ownership. Contrary to that idea, this is an attempt in which the capacity of watermarking is improved by embedding huge amount of watermark efficiently in the less quantity of image pixels. The core idea behind the proposed approach is to select watermarkable pixels from the host image based on the census transform and hamming distance followed by the embedding which is done by proposed spectral decompositions, i.e., Hankel, Circulant and Topelitz spectral decomposition. Finally, a reliable watermark extraction scheme is developed which is free from the false-positive detection problem of singular values. The experimental evaluation demonstrates that the proposed scheme is expeditiously able to withstand a variety of extreme attacks and highly suitable for covert communications.


Digital watermarking Census transform Hamming distance Spectral decomposition 


  1. 1.
    Agarwal H, Atrey PK, Raman B (2015) Image watermarking in real oriented wavelet transform domain. Multimedia Tools and Applications 74(23):10883–10921CrossRefGoogle Scholar
  2. 2.
    Barni M, Bartolini F (2004) Watermarking systems engineering: enabling digital assets security and other applications. Marcel Dekker Inc., New YorkGoogle Scholar
  3. 3.
    Bhatnagar G, Raman B (2009a) Robust encryption based watermarking in fractional wavelet domain. Recent advances in multimedia signal processing and communications in the series studies in computational intelligence, vol 231. Springer, pp 375–416Google Scholar
  4. 4.
    Bhatnagar G, Raman B (2009b) A new reference watermarking scheme based on DWT-SVD. Computer Standards and Interfaces 31(5):1002–1013Google Scholar
  5. 5.
    Bhatnagar G, Wu QMJ (2013) Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform. Futur Gener Comput Syst 29(1):182–195CrossRefGoogle Scholar
  6. 6.
    Chitla A, Mohan MC (2016) An adaptive quin-tree decomposition (AQTD) technique in image authentication through Lossless Watermarking (LWM). Pattern Recognition and Image Analysis 26(1):69–81CrossRefGoogle Scholar
  7. 7.
    Deng C, Gao X, Li X, Tao D (2009) A local Tchebichef moments-based robust image watermarking. Signal Process 89(8):1531–1539CrossRefMATHGoogle Scholar
  8. 8.
    Flusser J, Zitova B, Suk T (2009) Moments and moment invariants in pattern recognition. Wiley, UKCrossRefMATHGoogle Scholar
  9. 9.
    Gray RM (2006) Toeplitz and circulant matrices: a review. Foundations and Trends in Communications and Information Theory 2(3):155–239CrossRefMATHGoogle Scholar
  10. 10.
    Guo J-M, Liu Y-F (2012) High capacity data hiding for Error-Diffused block truncation coding. IEEE Trans Image Process 21(12):4808–4818MathSciNetCrossRefGoogle Scholar
  11. 11.
    Hsia SC, Jou IC, Hwang SM (2002) A gray level watermarking algorithm using double layer hidden approach. IEICE Trans Fundam E85-A(2):463–471Google Scholar
  12. 12.
    Hu M (1962) Visual pattern recognition by moment invariants. IRE Transcations on Information Theory IT-8:179–187MATHGoogle Scholar
  13. 13.
    Huang HC, Fang WC (2010) Techniques and applications of intelligent multimedia data hiding. Telecommun Syst 44:241–51CrossRefGoogle Scholar
  14. 14.
    Irany BM, Guo XC, Hatzinakos D (2011) A high capacity reversible multiple watermarking scheme for medical images. Proc Int Conf Digital Signal Processing:1–6Google Scholar
  15. 15.
    Karner H, Schneid J, Ueberhuber CW (2003) Spectral decomposition of real circulant matrices. Linear Algebra Appl 367:301–311MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Korus P, Bialas J, Dziech A (2014) A new approach to high-capacity annotation watermarking based on digital fountain codes. Multimedia Tools and Applications 68 (1):59–77CrossRefGoogle Scholar
  17. 17.
    Kundur D, Hatzinakos D (2004) Towards robust logo watermarking using meltiresolution image fusion. IEEE Trans Math 6:185–197Google Scholar
  18. 18.
    Li L, Pan JS, Yuan X (2001) High-capacity Watermark Embedding Based on Invariant Regions of Visual Saliency. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E94-A(2):889–893CrossRefGoogle Scholar
  19. 19.
    Li L, Qian J, Pan JS (2011) Characteristic region based watermark embedding with RST invariance and high-capacity. AEU-International Journal of Electronics and Communications 65(5):435–442CrossRefGoogle Scholar
  20. 20.
    Lian S (2008) Multimedia content encryption: techniques and applications. Auerbach Publications, bostonMATHGoogle Scholar
  21. 21.
    Lin WH, Horng SJ, Kao TW, Fan P, Lee CL, Pan Y (2008) An efficient watermarking method based on significant difference of wavelet coefficient quantization. IEEE Trans Multimed 10(5):746–757CrossRefGoogle Scholar
  22. 22.
    Luk FT, Qiao S (2003) A fast singular value algorithm for Hankel matrices. Fast Algorithms for Structured Matrices: Theory and Applications, Contemporary Mathematics, American Mathematical Society 323:169–177MathSciNetCrossRefMATHGoogle Scholar
  23. 23.
    Pandey P, Kumar S, Singh SK (2014) A robust logo watermarking technique in divisive normalization transform domain. Multimedia Tools and Applications 72:2653–2677CrossRefGoogle Scholar
  24. 24.
    Run R-S, Horng S-J, Lai J-L, Kao T-W, Chen R-J (2012) An improved SVD-based watermarking technique for copyright protection. Expert Syst Appl 39 (1):673–689CrossRefGoogle Scholar
  25. 25.
    Satish K, Jayakar T, Tobin C, Madhavi K, Murali K (2004) Chaos based spread spectrum image steganography. IEEE Trans Consum Electron 50(2):587–590CrossRefGoogle Scholar
  26. 26.
    Singh AK, Dave M, Mohan A (2014) Hybrid technique for robust and imperceptible image watermarking in DWT-DCT-SVD domain. National Academy Science Letters 37(4):351–358CrossRefGoogle Scholar
  27. 27.
    Singh AK, Kumar B, Dave M, Mohan A (2014) Robust and imperceptible dual watermarking for telemedicine applications. Wirel Pers Commun 80(4):1415–1433CrossRefGoogle Scholar
  28. 28.
    Singh AK, Dave M, Mohan A (2015) Robust and secure multiple watermarking in wavelet domain. Journal of Medical Imaging and Health Informatics 5(2):406–414CrossRefGoogle Scholar
  29. 29.
    Singh AK, Dave M, Mohan A (2015) Multilevel encrypted text watermarking on medical images using spread-spectrum in DWT domain. Wireless Personal Communications: An International Journal 83(3):2133–2150CrossRefGoogle Scholar
  30. 30.
    Singh AK, Dave M, Mohan A (2016) Improved Hybrid Technique for Robust and Imperceptible Multiple Watermarking using Medical Images. Multimedia Tools and Applications 75:8381–8401CrossRefGoogle Scholar
  31. 31.
    Song C, Sudirman S, Merabti M (2012) A robust region-adaptive dual image watermarking technique. J Vis Commun Image Represent 23(3):549–568CrossRefGoogle Scholar
  32. 32.
    Strang G (1993). Wellesley-Cambridge Press, Introduction to Linear AlgebraGoogle Scholar
  33. 33.
    Tang L-L, Huang CT, Pan J-S, Liu C-Y (2015) Dual watermarking algorithm based on the Fractional Fourier Transform. Multimedia Tools and Applications 74 (12):4397–4413CrossRefGoogle Scholar
  34. 34.
    Wang J, Lian S, Wang J (2015) Hybrid additive multi-watermarking and decoding. Multimedia Systems 21(4):345–361CrossRefGoogle Scholar
  35. 35.
    Wu Y (2005) On the security of an SVD-based ownership watermarking. IEEE Transactions on Multimedia 7(4):624–627CrossRefGoogle Scholar
  36. 36.
    Zabih R, Woodfill J (1994) Non-parametric local transforms for computing visual correspondence. Proc European Conf Computer Vision:151–158Google Scholar
  37. 37.
    Zhang X, Li K (2005) Comments on an SVD-based watermarking scheme for protecting rightful ownership. IEEE Transactions Multimedia 7(3):593–594CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of MathematicsIndian Institute of Technology JodhpurJodhpurIndia

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