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A Noninvertible SVD Technique for Watermarking Video Sequences


Affiliations
1 Department of Computer Science, MIT College of Engineering, Pune, India
     

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Video watermarking has been proposed in recent years to solve the problem of illegal manipulation, copyright protection and distribution of digital video. Video Watermarking provides a means of forensic analysis for combating media piracy. In this paper, we present an effective, robust and imperceptible simulation of a video watermarking algorithm that is based on the algebraic transform of Singular Value Decomposition (SVD) where the watermark-bit information are embedded in the SVD-transformed video in a diagonal-wise fashion. The current implementation of this technology provides a forensic solution, in which each media provider marks each copy of a piece of content with a watermark specific to the consumer of the content (e.g. a distributor, a theater, etc.). In this case the provider can track pirated content back to the initial consumer. The paper also discusses the use of genetic and neural networks to be employed to optimize the watermarking requirements.

Keywords

Copyright Protection, Genetic Algorithms, SVD, Video Watermarking.
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  • A Noninvertible SVD Technique for Watermarking Video Sequences

Abstract Views: 235  |  PDF Views: 2

Authors

Meeta Kumar
Department of Computer Science, MIT College of Engineering, Pune, India
Snehal Dhokey
Department of Computer Science, MIT College of Engineering, Pune, India
Neha Kulkarni
Department of Computer Science, MIT College of Engineering, Pune, India
Jayshree Deokar
Department of Computer Science, MIT College of Engineering, Pune, India

Abstract


Video watermarking has been proposed in recent years to solve the problem of illegal manipulation, copyright protection and distribution of digital video. Video Watermarking provides a means of forensic analysis for combating media piracy. In this paper, we present an effective, robust and imperceptible simulation of a video watermarking algorithm that is based on the algebraic transform of Singular Value Decomposition (SVD) where the watermark-bit information are embedded in the SVD-transformed video in a diagonal-wise fashion. The current implementation of this technology provides a forensic solution, in which each media provider marks each copy of a piece of content with a watermark specific to the consumer of the content (e.g. a distributor, a theater, etc.). In this case the provider can track pirated content back to the initial consumer. The paper also discusses the use of genetic and neural networks to be employed to optimize the watermarking requirements.

Keywords


Copyright Protection, Genetic Algorithms, SVD, Video Watermarking.