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dc.date.accessioned 2012-10-09T12:30:04Z
dc.date.available 2012-10-09T12:30:04Z
dc.date.issued 2012
dc.identifier.uri http://hdl.handle.net/10915/22064
dc.description.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 en
dc.format.extent p. 123-132 es
dc.language en es
dc.title Automatic stereoscopic video object-based watermarking using qualified significant wavelet trees en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/journal/journal34/papers/JCST-Oct12-5.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Ntalianis, Klimis S. es
sedici.creator.person Tzouveli, Paraskevi D. es
sedici.creator.person Drigas, Athanasios S. es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.decs Procesamiento de Imagen Asistida por Computador es
sedici.subject.keyword video object (VO) en
sedici.subject.keyword visually recognizable watermark pattern en
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 12, no. 3 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)