DWT-Based Blind Video Watermarking Using Image Scrambling Technique

  • C. N. SujathaEmail author
  • P. Sathyanarayana
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 106)


This paper addresses an Arnold Transform based gray image embedding in video using Discrete Wavelet Transform (DWT). In the proposed scheme, the video is authenticated with different parts of watermark by using histogram-based scene change technique. Each frame is estranged into three planes. DWT is applied to selective plane in each frame to putrefy into sub-bands. The chosen secrete image is separated into 8-bit planes. Bit plane image is further scrambled using an Arnold transform to get high protection of watermark. In this scheme, embedding is done in mid and high-frequency coefficients of DWT without mortifying the perceptual quality of video. Hidden image is extracted from the marked video by following the inverse processing steps. Robustness is tested by subjecting the marked video to various video processing and image processing attacks. Simulation results show that the proposed scheme is highly resistant to frame averaging, frame dropping, and noise attacks.


Watermark Scene change analysis DWT PSNR CF 


  1. 1.
    Mondal, B., Sinha, N., Mandal, T.: A secure image encryption algorithm using LFSR and RC4 key stream generator. In: Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics, SIST, vol. 43, pp. 227–237. Springer, India (2016)Google Scholar
  2. 2.
    Zhou, R.-G., Sun, Y.-J., Fan, P.: Quantum image gray-code and bitplane scrambling. Quantum Inf. Process. 14(5), 1717–1734 (2015)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Li, Y., Wang, C., Chen, H.: A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation. Opt. Lasers Eng. 90, 238–246 (2017)CrossRefGoogle Scholar
  4. 4.
    Abbas, N.A.M.: Image encryption based on independent component analysis and Arnolds cat map. Egypt. Inf. J. 17(1), 139–146 (2016)Google Scholar
  5. 5.
    Zou, J., Ward, R.K., Qi, D.: A new digital image scrambling method based on Fibonacci numbers. In: Proceedings of the 2004 International Symposium on Circuits and Systems, ISCAS’04, vol. 3, pp. III-965 (2004)Google Scholar
  6. 6.
    Inoue, H., Miyazaki, A., Araki, T., Kastura, T.: A digital watermark method using the wavelet transform for video data. IEICE Trans. Fundam. E38-A(1) (2000)Google Scholar
  7. 7.
    Swanson, M.D., Zhu, B., Tewfik, A.H.: Multiresolution scene-based video watermarking using perceptual models. IEEE J. Select. Areas Commun. 16(4) (1998)Google Scholar
  8. 8.
    Parah, S.A., Sheikh, J.A., Assad, U.I., Bhat, G.M.: Realisation and robustness evaluation of a blind spatial domain watermarking technique. Int. J. Electron. (2016)Google Scholar
  9. 9.
    Zhao, X., Ho, A.T.S.: An introduction to robust transform based image watermarking techniques. In: Intelligent Multimedia Analysis for Security Applications. Studies in Computational Intelligence, vol. 282. Springer, Berlin, Heidelberg (2010)Google Scholar
  10. 10.
    Pradhan, C., Saha, B.J., Kabi, K.K., Bisoi, A.K.: Blind watermarking techniques using DCT and Arnold 2D cat map for color images. In: International Conference on Communication and Signal Processing, pp. 027–030 (2014)Google Scholar
  11. 11.
    Priya, P., Tanvi, G., Nikita, P., Ankita, T.: Digital video watermarking using modified LSB and DCT technique. Int. J. Res. Eng. Technol. (IJERT) 3(4), 630–634 (2014)Google Scholar
  12. 12.
    Essaouabi, A., Regragui, F., Ibnelhaj, E.: A blind wavelet-based digital watermarking for video. Int. J. Video Image Process. Netw. Secur. (IJVIPNS) 9(9), 37–41 (2009)Google Scholar
  13. 13.
    Hussein, J., Mohammed, A.: Robust video watermarking using multi band wavelet transform. Int. J. Comput. Sci. Issues (IJCSI) 6(1), 44–59 (2009)Google Scholar
  14. 14.
    Lin, W.-H., Wang, Y.-R., Horng, S.-J., Kao, T.-W., Pan, Y.: A blind watermarking method using maximum wavelet coefficient quantization. Expert Syst. Appl. (Elsevier) 36, 11509–11516 (2009)Google Scholar
  15. 15.
    Qian, H., Tian, L., Li, C.: Robust blind image watermarking algorithm based on singular value quantization. In: ICIMCS’16. ACM (2016)Google Scholar
  16. 16.
    Chang, C.-S., Shen, J.-J.: Features classification forest: a novel development that is adaptable to robust blind watermarking techniques. IEEE Trans. Image Process. IEEE Signal Process. Soc. (2017)Google Scholar
  17. 17.
    Gaobo, Y., Xingming, S., Xiaojing, W.: A genetic algorithm based video watermarking in the DWT domain. In: International Conference on Computational Intelligence and Security. IEEE (2006)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of ECESNISTHyderabadIndia
  2. 2.Department of ECEAITSTirupatiIndia

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