Video object watermarking based on moments

Tzouveli, PK; Ntalianis, KS; Kollias, SD

dc.contributor.author	Tzouveli, PK	en
dc.contributor.author	Ntalianis, KS	en
dc.contributor.author	Kollias, SD	en
dc.date.accessioned	2014-03-01T02:44:21Z
dc.date.available	2014-03-01T02:44:21Z
dc.date.issued	2006	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31773
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Copyrights	en
dc.subject.other	Digital watermarking	en
dc.subject.other	Estimation	en
dc.subject.other	Functions	en
dc.subject.other	Pattern recognition	en
dc.subject.other	Robustness (control systems)	en
dc.subject.other	Human video object detectors	en
dc.subject.other	Video object authentication	en
dc.subject.other	Video object watermarking	en
dc.subject.other	Neural networks	en
dc.title	Video object watermarking based on moments	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/11738695_10	en
heal.identifier.secondary	http://dx.doi.org/10.1007/11738695_10	en
heal.language	English	en
heal.publicationDate	2006	en
heal.abstract	A robust video object based watermarking scheme, based on Zernike and Hu moments, is proposed in this paper. Firstly, a human video object detector is applied to the initial image. Zernike and the Hu moments of each human video object are estimated and an invariant function for watermarking is incorporated. Then, the watermark is generated modifying the moment values of each human video object. In the detection scheme, a neural network classifier is initially used in order to extract possible watermarked human video objects from each received input image. Then, a watermark detection procedure is applied for video object authentication. A full experiment confirms the promising performance of the proposed scheme. Furthermore, the performances of the two types of moments are extensively investigated under several attacks, verifying the robustness of Zernike moments comparing to Hu moments. © Springer-Verlag Berlin Heidelberg 2006.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/11738695_10	en
dc.identifier.isi	ISI:000238283100010	en
dc.identifier.volume	3893 LNCS	en
dc.identifier.spage	68	en
dc.identifier.epage	75	en