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Detecting Removed Object from Video with Stationary Background

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The International Workshop on Digital Forensics and Watermarking 2012 (IWDW 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7809))

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Abstract

This paper presents a method for detecting the removed object in video captured by stationary camera. The method is based on an observation that the removed object, while not distinguishable by human eyes, leaves artifacts that can be detected by computers. In this paper, the block based motion estimation method is employed to extract motion information from adjacent video frames. Then the magnitude and orientation of the motion vectors are used to differentiate the authentic region and the forged region. By exploring the discrepancies in motion vectors, the position of the removed object can be revealed. The efficiency of the proposed method is demonstrated by experiments.

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Author information

Authors and Affiliations

  1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Leida Li, Xuewei Wang & Wei Zhang

  2. Shanghai Key Laboratory of Integrate Administration Technologies for Information Security, Shanghai, 200240, China

    Leida Li

  3. School of Information Science and Engineering, Hunan University, Changsha, 410082, China

    Gaobo Yang

  4. Department of Neurosurgery, China-Japan Union Hospital, Jilin University, Changchun, 130033, China

    Guozhang Hu

Authors
  1. Leida Li
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  2. Xuewei Wang
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  3. Wei Zhang
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  4. Gaobo Yang
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  5. Guozhang Hu
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Editor information

Editors and Affiliations

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

    Yun Q. Shi

  2. Multimedia Security Lab, Korea University, 136-701, Seoul, South Korea

    Hyoung-Joong Kim

  3. Signal Theory and Communications Department, University of Vigo, 36310, Vigo, Spain

    Fernando Pérez-González

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© 2013 Springer-Verlag Berlin Heidelberg

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Li, L., Wang, X., Zhang, W., Yang, G., Hu, G. (2013). Detecting Removed Object from Video with Stationary Background. In: Shi, Y.Q., Kim, HJ., Pérez-González, F. (eds) The International Workshop on Digital Forensics and Watermarking 2012. IWDW 2012. Lecture Notes in Computer Science, vol 7809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40099-5_20

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  • DOI: https://doi.org/10.1007/978-3-642-40099-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40098-8

  • Online ISBN: 978-3-642-40099-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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