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An Effective Video Bootleg Detection Algorithm Based on Noise Analysis in Frequency Domain

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Computer Vision and Image Processing (CVIP 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1147))

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Abstract

Nowadays everybody has mobile phone, tablet and other video capturing devices containing high quality cameras. This enable them to recapture the videos from other imitating media such as projectors, the LCD screens etc. Recently, video piracy has become a major criminal enterprise. So, in order to combat this uprising threat of video piracy, content owners and the enforcement agencies such as Motion Pictures Association, have to continuously work hard on video copyright protection laws. This is one of the major reasons why digital forensics has considered recaptured video detection an important problem. This paper presents a simple and an effective mechanism for recaptured video detection which is based upon the noise analysis in the frequency domain. The features adopted are mean, variance, kurtosis and mean square error. These features are calculated on the mean strip extracted from logarithmic magnitude Fourier plot on complete video length.

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Author information

Authors and Affiliations

  1. National Institute of Technology, New Delhi, India

    Preeti Mehta & Sushila Maheshkar

  2. Netaji Subhas Institute of Technology, New Delhi, India

    Vikas Maheshkar

Authors
  1. Preeti Mehta
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  2. Sushila Maheshkar
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  3. Vikas Maheshkar
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Corresponding author

Correspondence to Preeti Mehta .

Editor information

Editors and Affiliations

  1. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Neeta Nain

  2. Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Santosh Kumar Vipparthi

  3. Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

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Mehta, P., Maheshkar, S., Maheshkar, V. (2020). An Effective Video Bootleg Detection Algorithm Based on Noise Analysis in Frequency Domain. In: Nain, N., Vipparthi, S., Raman, B. (eds) Computer Vision and Image Processing. CVIP 2019. Communications in Computer and Information Science, vol 1147. Springer, Singapore. https://doi.org/10.1007/978-981-15-4015-8_20

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  • DOI: https://doi.org/10.1007/978-981-15-4015-8_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4014-1

  • Online ISBN: 978-981-15-4015-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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