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

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...

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Autores principales: Ntalianis, Klimis S., Tzouveli, Paraskevi D., Drigas, Athanasios S.
Formato: Articulo
Lenguaje:Inglés
Publicado: 2012
Materias:
Ciencias Informáticas
Procesamiento de Imagen Asistida por Computador
video object (VO)
visually recognizable watermark pattern
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22064
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct12-5.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22064
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Procesamiento de Imagen Asistida por Computador
video object (VO)
visually recognizable watermark pattern
spellingShingle Ciencias Informáticas
Procesamiento de Imagen Asistida por Computador
video object (VO)
visually recognizable watermark pattern
Ntalianis, Klimis S.
Tzouveli, Paraskevi D.
Drigas, Athanasios S.
Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
topic_facet Ciencias Informáticas
Procesamiento de Imagen Asistida por Computador
video object (VO)
visually recognizable watermark pattern
description 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 (HL<sub>3</sub> , HL<sub>2</sub>), (LH<sub>3</sub>, LH<sub>2</sub>) and (HH<sub>3</sub>, HH<sub>2</sub>). 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
format Articulo
Articulo
author Ntalianis, Klimis S.
Tzouveli, Paraskevi D.
Drigas, Athanasios S.
author_facet Ntalianis, Klimis S.
Tzouveli, Paraskevi D.
Drigas, Athanasios S.
author_sort Ntalianis, Klimis S.
title Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
title_short Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
title_full Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
title_fullStr Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
title_full_unstemmed Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
title_sort automatic stereoscopic video object-based watermarking using qualified significant wavelet trees
publishDate 2012
url http://sedici.unlp.edu.ar/handle/10915/22064
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct12-5.pdf
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AT tzouveliparaskevid automaticstereoscopicvideoobjectbasedwatermarkingusingqualifiedsignificantwavelettrees
AT drigasathanasioss automaticstereoscopicvideoobjectbasedwatermarkingusingqualifiedsignificantwavelettrees
bdutipo_str Repositorios
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