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Surveillance Video Authentication Using Universal Image Quality Index of Temporal Average

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Digital Forensics and Watermarking (IWDW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11378))

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Abstract

Inter-frame forgery is a common type of surveillance video forgery where a tampered process occurs in a temporal domain such as frame deletion, insertion, and shuffling. However, there are a number of methods that have been proposed for detecting this type of tampering, most of the methods have been found to be deficient in terms of either accuracy or running time. In this paper, a new approach is proposed as an efficient method for detecting frame deletion, insertion, and shuffling attacks. Firstly, the video is extracted into frames and the temporal average for each non-overlapping subsequence of frames is computed for examination instead of exhaustive checking which can be reduced the running time. Then, the universal image quality index is used for detecting the inter-frame forgery and determining its location. The experimental results show the efficiency of the proposed method for detecting inter-frame forgery with high accuracy and low running time.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China [grant numbers 61471141, 61361166006, 61301099]; Key Technology Program of Shenzhen, China, [grant number JSGG20160427185010977]; Basic Research Project of Shenzhen, China [grant number JCYJ20150513151706561].

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

    Sondos Fadl, Qi Han & Qiong Li

  2. Faculty of Computers and Information, Menoufia University, Menofia, Egypt

    Sondos Fadl

Authors
  1. Sondos Fadl
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  2. Qi Han
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  3. Qiong Li
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Corresponding authors

Correspondence to Sondos Fadl or Qi Han .

Editor information

Editors and Affiliations

  1. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Chang D. Yoo

  2. New Jersey Institute of Technology, Newark, NJ, USA

    Yun-Qing Shi

  3. Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

  4. University of Florence, Florence, Italy

    Alessandro Piva

  5. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Gwangsu Kim

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Fadl, S., Han, Q., Li, Q. (2019). Surveillance Video Authentication Using Universal Image Quality Index of Temporal Average. In: Yoo, C., Shi, YQ., Kim, H., Piva, A., Kim, G. (eds) Digital Forensics and Watermarking. IWDW 2018. Lecture Notes in Computer Science(), vol 11378. Springer, Cham. https://doi.org/10.1007/978-3-030-11389-6_25

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  • DOI: https://doi.org/10.1007/978-3-030-11389-6_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11388-9

  • Online ISBN: 978-3-030-11389-6

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