Abstract
In many courts, surveillance videos are used as important legal evidence. Nevertheless, little research is concerned with forgery of surveillance videos. In this paper, we present a forgery detection system for surveillance videos. We analyze the characteristic of surveillance videos. Subsequently, forgeries mainly occur to the surveillance videos are investigated. To identify both RGB and infrared video, Sensor Pattern Noise (SPN) for each video is transformed by Minimum Average Correlation Energy (MACE) filter. Manipulations on the given video are detected by estimating scaling factor and calculating correlation coefficient. Experimental results demonstrate that the proposed scheme is appropriate to identify forgeries of surveillance video.
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Notes
- 1.
We adopt “correlation plain” which is originated in the field of optical filtering [5].
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Acknowledgment
This research project was supported by Ministry of Culture, Sports and Tourism (MCST) and from Korea Copyright Commission in 2011, WCU (World Class University) program (Project No: R31-30007), and NRL (National Research Lab) program (No. R0A-2007-000-20023-0) under the National Research Foundation of Korea and funded by the Ministry of Education, Science and Technology of Korea
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Hyun, DK., Lee, MJ., Ryu, SJ., Lee, HY., Lee, HK. (2013). Forgery Detection for Surveillance Video. In: The Era of Interactive Media. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3501-3_3
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DOI: https://doi.org/10.1007/978-1-4614-3501-3_3
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