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

Authors

  • 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

Keywords:

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

Abstract

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

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References

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Published

2012-10-01

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 https://journal.info.unlp.edu.ar/JCST/article/view/646

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Section

Original Articles