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A review on robust video copy detection

A review on robust video copy detection 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Multimedia Information Retrieval Springer Journals

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Computer Science; Multimedia Information Systems; Information Storage and Retrieval; Information Systems Applications (incl.Internet); Data Mining and Knowledge Discovery; Image Processing and Computer Vision; Database Management
ISSN
2192-6611
eISSN
2192-662X
DOI
10.1007/s13735-018-0159-x
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of Multimedia Information RetrievalSpringer Journals

Published: Aug 31, 2018

References