Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees


  • Klimis S. Ntalianis National Technical University of Athens, Electrical and Computer Engineering Department, 15773, Athens, Greece
  • Paraskevi D. Tzouveli National Technical University of Athens, Electrical and Computer Engineering Department, 15773, Athens, Greece
  • Athanasios S. Drigas Net Media Lab, NCSR Demokritos, Athens, Greece


Video object (VO), Shape Adaptive Discrete Wavelet Transform, Visually recognizable watermark pattern, Qualified Significant Wavelet Tree


In this paper a fully automatic scheme for embedding visually recognizable watermark patterns to video objects is proposed. The architecture consists of 3 main modules. During the first module unsupervised video object extraction is performed, by analyzing stereoscopic pairs of frames. In the second module each video object is decomposed into three levels with ten subbands, using the Shape Adaptive Discrete Wavelet Transform (SA-DWT) and three pairs of subbands are formed (HL3 , HL2), (LH3, LH2) and (HH3, HH2). Next Qualified Significant Wavelet Trees (QSWTs) are estimated for the specific pair of subbands with the highest energy content. QSWTs are derived from the Embedded Zerotree Wavelet (EZW) algorithm and they are high-energy paths of wavelet coefficients. Finally during the third module, visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the inverse SA-DWT is applied to provide the watermarked video object. Performance of the proposed video object watermarking system is tested under various signal distortions such as JPEG lossy compression, sharpening, blurring and adding different types of noise. Furthermore the case of transmission losses for the watermarked video objects is also investigated. Experimental results on real life video objects indicate the efficiency and robustness of the proposed scheme


Download data is not yet available.


[1] ISO/IEC 14496-2:2004 Information technology - Coding of audio-visual objects - Part 2: Visual, 2004.
[2] R. G. van Schyndel, A. Z. Tirkel, and C. F. Osborne, “A digital watermark,” in Proceedings of the IEEE Int. Conf. Image Processing, vol.2, pp. 86-90, 1994.
[3] N. Nikolaidis, and I. Pitas, “Copyright protection of images using robust digital signatures,” in Proceedings IEEE Int. Conf. Acoustics, Speech and Signal Processing, vol.4, pp. 2168-2171, May 1996.
[4] R. Wolfgang and E. Delp, “A watermark for digital image,” in Proceedings Int. Conf. Image Processing, vol.3, pp. 211-214, 1996.
[5] J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Trans. Image Processing, vol.6, pp. 1673-1687, Dec.1997.
[6] C.-T. Hsu and J.-L. Wu, “DCT-based watermarking for video,” IEEE Trans. Consumer Electronics, vol.44, pp. 206-216, Feb. 1998.
[7] M.-S. Hsieh, D.-C. Tseng, and Y.-H. Huang, “Hiding Digital Watermarks Using Multiresolution Wavelet Transform,” IEEE Trans. Industrial Electronics, vol. 48, no. 5, pp. 875-882, Oct. 2001.
[8] W. Zhu, Z. Xiong, and Y.-Q. Zhang, “Multiresolution watermarking for images and video,” IEEE Trans. Circuits and Systems for Video Technology, vol. 9, no.4, pp. 545-550, June 1999.
[9] H. Daren, L. Jiufen, H. Jiwu, and L. Hongmei, “A DWT-based image watermarking algorithm,” in Proceedings IEEE Int. Conf. Multimedia and Expo, Tokyo, Japan, 22-25 August, 2001.
[10] X. Wu, W. Zhu, Z. Xiong, and Y.-Q. Zhang, “Object-based multiresolution watermarking of images and video,” in Proceedings IEEE Int. Sym. Circuits and Systems, Geneva, Switzerland, May 28-31, 2000.
[11] P. Bas, and B. Macq, “A new video-object watermarking scheme robust to object manipulation,” in Proceedings IEEE Int. Conf. Image Processing, Vol. 2, pp. 526 –529, Oct. 2001.
[12] M. D. Swanson, B. Zhu, B. Chau, and A. H. Tewfik, “Object-based transparent video watermarking,” in Proceedings IEEE Workshop on Multimedia Signal Processing, New Jersey, USA, June 23-25, 1997.
[13] C.-S. Lu, and H.-Y. M. Liao, “Oblivious cocktail watermarking by sparse code shrinkage: a regional- and global-based scheme”, in Proceedings IEEE Int. Conf. Image Processing, Vancouver, Canada, vol. III, pp. 13-16, Sept. 10-13, 2000.
[14] A. Nikolaidis and I. Pitas, “Region-Based Image Watermarking,” IEEE Trans. Image Processing, Vol. 10, No. 11, Nov. 2001.
[15] L. Lia,, J. Qiana,, and J.-S. Panb, “Characteristic region based watermark embedding with RST invariance and high capacity,” Elsevier International Journal of Electronics and Communications, Vol. 65, No. 5, May 2011.
[16] C. Deng, X. Gao, X. Li and D. Tao, “Robust Image Watermarking Based on Feature Regions,” Studies in Computational Intelligence, Springer, Vol. 346, 2011.
[17] X. Wang and Z. Guo, “A robust content-based watermarking scheme,” IEEE International Workshop on Multimedia Signal Processing, 2009.
[18] L. Yang, R. Ni and Y. Zhao, “Segmentation-based Image Authentication and Recovery Scheme Using Reference Sharing Mechanism,” American Journal of Engineering and Technology Research, Vol. 11, No.6, 2011.
[19] M.K. Kundu and S. Das, “Lossless ROI Medical ImageWatermarking Technique with Enhanced Security and High Payload Embedding,” International Conference on Pattern Recognition, Turkey, 2010.
[20] O. M. Al-Qershi and B. E. Khoo, “ROI–based Tamper Detection and Recovery for Medical Images Using Reversible Watermarking Technique,” IEEE International Conference on Information Theory and Information Security, Beijing, China, 2010.
[21] R.-V. Schyndel, “A Hardware-based Surveillance Video Camera Watermark ,” International Conference on Digital Image Computing: Techniques and Applications, Sydney, Australia, 2010.
[22] L. Coria, P. Nasiopoulos and R. Ward, “A Region-Specific QIM-Based Watermarking Scheme for Digital Images,” IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, Bilbao, Spain, May 2009.
[23] K. S. Ntalianis, N. D. Doulamis, A. D. Doulamis, and S. D. Kollias, “Tube-Embodied Gradient Vector Flow Fields for Unsupervised Video Object Plane (VOP) Segmentation,” in Proceedings IEEE Int. Conf. Image Processing, Thessaloniki, Greece, October 2001.
[24] S. Li, and W. Li, “Shape-Adaptive Discrete Wavelet Transforms for Arbitrarily Shaped Visual Object Coding,” IEEE Trans. Circuits and Systems for Video Technology, vol. 10, no.5, pp. 725-743, August 2000.
[25] M. Shapiro, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Trans. Signal Processing, vol.41, pp. 3445-3462, Dec. 1993.
[26] A. D. Doulamis, N. D. Doulamis, K. S. Ntalianis and S. D. Kollias, “Efficient Unsupervised Content-Based Segmentation in Stereoscopic Video Sequence,” in Intern. Journal on Artificial Intelligence Tools, vol. 8, no.6, 2000.
[27] L. Garrido, F. Marques, M. Pardas, P. Salembier and V. Vilaplana, “A Hierarchical Technique for Image Sequence Analysis,” in Proc. of Workshop on Image Analysis for Multim. Interactive Services (WIAMIS), pp. 13-20, Louvain-la-Neuve, Belgium, June 1997.
[28] C. Xu, and J. L. Prince, “Snakes, Shapes, and Gradient Vector Flow,” IEEE Trans. Image Processing, Vol. 7, No. 3, pp. 359-369, March 1998.
[29] C.-T. Hsu and J.-L. Wu, “Multiresolution watermarking for digital images,” IEEE Trans. Consumer Electronics, vol. 45, pp. 1097–101, Aug. 1998.
[30] V. Weerackody, C. Podilchuk, and A. Estrella, “Transmission of JPEG-Coded Images over Wireless Channels,” Bell Labs Technical Journal, Autumn 1996.




How to Cite

Ntalianis, K. S., Tzouveli, P. D., & Drigas, A. S. (2012). Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees. Journal of Computer Science and Technology, 12(03), p. 123–132. Retrieved from



Original Articles