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2D approaches to 3D watermarking: State-of-the-art and perspectives

  • CNRS SAMOVAR UMR 5157
  • University 'Politehnica' of Bucharest

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

With the advent of the Information Society, video, audio, speech, and 3D media represent the source of huge economic benefits. Consequently, there is a continuously increasing demand for protecting their related intellectual property rights. The solution can be provided by robust watermarking, a research field which exploded in the last 7 years. However, the largest part of the scientific effort was devoted to video and audio protection, the 3D objects being quite neglected. In the absence of any standardisation attempt, the paper starts by summarising the approaches developed in this respect and by further identifying the main challenges to be addressed in the next years. Then, it describes an original oblivious watermarking method devoted to the protection of the 3D objects represented by NURBS (Non-uniform Rational B-Spline) surfaces. Applied to both free form objects and CAD models, the method exhibited very good transparency (no visible differences between the marked and the unmarked model) and robustness (with respect to both traditional attacks and to NURBS processing).

Original languageEnglish
Title of host publicationImage Processing
Subtitle of host publicationAlgorithms and Systems, Neural Networks, and Machine Learning - Proceedings of SPIE-IS and T Electronic Imaging
PublisherSPIE
ISBN (Print)0819461040, 9780819461049
DOIs
Publication statusPublished - 1 Jan 2006
Externally publishedYes
EventImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning - San Jose, CA, United States
Duration: 16 Jan 200618 Jan 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6064
ISSN (Print)0277-786X

Conference

ConferenceImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Country/TerritoryUnited States
CitySan Jose, CA
Period16/01/0618/01/06

Keywords

  • 3D informed watermarking
  • NURBS representation
  • Robustness
  • Transparency

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