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Information 2018, 9(12), 301;

An Inter-Frame Forgery Detection Algorithm for Surveillance Video

1,2,*, 2,* and 3
College of Information Engineering, Ningbo Dahongying University, Ningbo 315175, China
CKC Software Laboratory, Ningbo University, Ningbo 315211, China
School of Electronics and Information Engineering, Ningbo University of Technology, Ningbo 315211, China
Authors to whom correspondence should be addressed.
Received: 16 August 2018 / Revised: 8 November 2018 / Accepted: 20 November 2018 / Published: 28 November 2018
PDF [3792 KB, uploaded 28 November 2018]


Surveillance systems are ubiquitous in our lives, and surveillance videos are often used as significant evidence for judicial forensics. However, the authenticity of surveillance videos is difficult to guarantee. Ascertaining the authenticity of surveillance video is an urgent problem. Inter-frame forgery is one of the most common ways for video tampering. The forgery will reduce the correlation between adjacent frames at tampering position. Therefore, the correlation can be used to detect tamper operation. The algorithm is composed of feature extraction and abnormal point localization. During feature extraction, we extract the 2-D phase congruency of each frame, since it is a good image characteristic. Then calculate the correlation between the adjacent frames. In the second phase, the abnormal points were detected by using k-means clustering algorithm. The normal and abnormal points were clustered into two categories. Experimental results demonstrate that the scheme has high detection and localization accuracy. View Full-Text
Keywords: surveillance video; video forensics; inter-frame forgery; 2-D phase congruency; k-means clustering surveillance video; video forensics; inter-frame forgery; 2-D phase congruency; k-means clustering

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Li, Q.; Wang, R.; Xu, D. An Inter-Frame Forgery Detection Algorithm for Surveillance Video. Information 2018, 9, 301.

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