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A review on robust video copy detection

  • Alongbar Wary
  • Arambam Neelima
Trends and Surveys
  • 63 Downloads

Abstract

The unprecedented escalation and proliferation of digital multimedia and Internet technology have triggered the enormous copyright infringement issues and tampering of digital content. Detection or localization of copy–paste forgery of digital content and distinguishing between original and manipulated video have become a weighty challenge at the present era of multimedia technology. Several distortions such as rotation, scaling and gamma correction are applied into an original video by an adversary to manipulate the original video for copyright infringement. Due to the emergence of ubiquitous digital videos on the Internet and to surpass the challenges, various copy detection schemes have been introduced by several researchers. Many real-time applications such as detection of duplicate Web videos and monitoring of real-time TV commercial media content over multi-broadcast channels require the robust copy detection approach for high security purpose. The other applications include the rapid advancement of video navigation and editing technology such as finding the opening sequence of a TV show and combining or editing similar versions of the same video for copyright infringement. This paper depicts a comprehensive overview of robust visual hashing to identify similar video contents for digital piracy detection, which overcomes the demerits of conventional cryptographic hash functions and watermarking. The paramount goal of this scheme is to generate the perceptual hash code of fixed size of length from video segments which are robust against distinct distortions or attacks such as scaling, rotation, compression, frame rate change, frame dropping, contrast enhancement, etc., made by an adversary. Besides, in this paper, distinct state-of-the-art schemes used for copy detection have been studied thoroughly and classified based on the methodology they have implemented.

Keywords

Robust visual hashing Video copy detection Cryptographic hash Watermarking 

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringNIT NagalandChumukedima, DimapurIndia

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