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

In this paper a 3-module automatic watermarking system is proposed, which embeds visually recognizable patterns to video objects (VO). During the first module efficient unsupervised video object extraction is performed. In the second module the DWT is applied to the extracted VO to produce ten subbands and three pairs of subbands are formed. Next QSWT are estimated for the pair of subbands with the highest energy content. Finally in the third module visually recognizable patterns are embedded to the coefficients of the highest energy QSWT and the IDWT is applied to provide the watermarked VO. The performance of the proposed system has been tested under various signal distortions producing very promising results.