An automatic scheme for stereoscopic video object-based watermarking using qualified significant wavelet trees

Ntalianis, KS; Doulamis, AD; Doulamis, ND; Kollias, SD

dc.contributor.author	Ntalianis, KS	en
dc.contributor.author	Doulamis, AD	en
dc.contributor.author	Doulamis, ND	en
dc.contributor.author	Kollias, SD	en
dc.date.accessioned	2014-03-01T02:49:12Z
dc.date.available	2014-03-01T02:49:12Z
dc.date.issued	2002	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34406
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0036448431&partnerID=40&md5=b3b20b8891bce6b036b786c545a41e71	en
dc.subject.other	Algorithms	en
dc.subject.other	Digital watermarking	en
dc.subject.other	Feature extraction	en
dc.subject.other	Image compression	en
dc.subject.other	Image segmentation	en
dc.subject.other	Signal distortion	en
dc.subject.other	Wavelet transforms	en
dc.subject.other	Embedded zerotree wavelet	en
dc.subject.other	Qualified significant wavelet trees	en
dc.subject.other	Video object extraction	en
dc.subject.other	Image coding	en
dc.title	An automatic scheme for stereoscopic video object-based watermarking using qualified significant wavelet trees	en
heal.type	conferenceItem	en
heal.publicationDate	2002	en
heal.abstract	In this paper a fully automatic system 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. Then each video object is decomposed into three levels with ten subbands, using the Discrete Wavelet Transform (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 that contains the highest energy content compared to the other two pairs. QSWTs are derived from the Embedded Zerotree Wavelet (EZW) algorithm and they are high-energy coefficient paths within the selected pair of subbands. Finally during the third module, visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the inverse DWT is applied to provide the watermarked video object. The 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. Experimental results on real life stereoscopic images are presented to indicate the efficiency and robustness of the proposed scheme.	en
heal.journalName	IEEE International Conference on Image Processing	en
dc.identifier.volume	3	en
dc.identifier.spage	III/501	en
dc.identifier.epage	III/504	en