A Novel Un-compressed Video Watermarking in Wavelet Domain Using Fuzzy Inference System

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 28)

Abstract

In this paper, human visual system (HVS) characteristics are modeled using Mamdani fuzzy inference system (FIS) for robust un-compressed video watermarking technique in discrete wavelet transform (DWT) domain. The video sequence is decomposed into frames and converted into YCbCr color space. Two HVS characteristics namely edge sensitivity and contrast sensitivity are computed for each luminance component (Y) of the frame. These two computed values are fed as input to the FIS. The output of the FIS is a weighting factor which is used to embed the watermark into the frame. For embedding purpose a binary watermark is embedded into the LL3 sub-band coefficients of the video sequence. To study the robustness of proposed scheme various video processing attacks are performed. Experimental results show that proposed video watermarking scheme is highly robust and obtain good perceptual quality.

Keywords

Digital video watermarking DWT FIS HVS 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lin, D.-T., Liao, G.-J.: Embedding Watermarks in Compressed Video using Fuzzy C-Means Clustering. In: Proceedings of IEEE International Conference on Systems (2008)Google Scholar
  2. 2.
    Raghavendra, K., Chetan, K.R.: A Blind and Robust Watermarking Scheme with Scrambled Watermark for Video Authentication. In: Proceedings of IEEE International Conference onInternet Multimedia Services Architecture and Applications (2009)Google Scholar
  3. 3.
    Wang, Y., Pearmain, A.: Blind MPEG-2 Video Watermarking Robust Against Geometric Attacks: A Set of Approaches in DCT Domain. IEEE Transactions on Image Processing 15(6) (2006)Google Scholar
  4. 4.
    Lee, X., Zhang, Y.-Q., Leon-Garcia, A.: Image And Video Reconstruction Using Fuzzy Logic. In: Proceedings of IEEE International Conference on Global Telecommunications Conference (1993)Google Scholar
  5. 5.
    Masoumi, M., Amiri, S.: A blind scene-based watermarking for video copyright protection. International Journal of Electronics and Communications (2013)Google Scholar
  6. 6.
    Al-Taweel, S.A.M., Sumari, P.: Robust Video Watermarking Based On 3D-DWT Domain. In: Proceedings of IEEE International Conference on TENCON (2009)Google Scholar
  7. 7.
    Da-Wen, X.: A Blind Video Watermarking Algorithm Based on 3D Wavelet Transform. In: Proceedings of IEEE International Conference on Computational Intelligence and Security (2007)Google Scholar
  8. 8.
    Yassin, N.I., Salem, N.M., Adawy, M.I.E.: Block Based VideoWatermarking Scheme Using Wavelet Transform and Principle Component Analysis. IJCSI International Journal of Computer Science Issues 9(1), 3 (2012)Google Scholar
  9. 9.
    Sinha, S., Bardhan, P., Pramanick, S., Jagatramka, A., Kole, D.K., Chakraborty, A.: Digital Video Watermarking using Discrete Wavelet Transform and Principal Component Analysis. International Journal of Wisdom Based Computing 1(2) (2011)Google Scholar
  10. 10.
    Lande, P.U., Talbar, S.N., Shinde, G.N.: A Fuzzy Logic Approach to Encrypted Watermarking for Still Images in Wavelet Domain on FPGA. International Journal of Signal Processing, Image Processing and Pattern Recognition 3(2) (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Ajay Kumar Garg Engineering CollegeGhaziabadIndia

Personalised recommendations