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Zhenzhen Zhang, Jianjun Hou, Qinglong Ma and Zhaohong Li Efficient video frame insertion and deletion detection based on inconsistency of correlations between local binary pattern coded frames Security and Communication Networks 8

Version of Record online: 10 MAR 2014 | DOI: 10.1002/sec.981

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Frame insertion and deletion are common inter-frame forgery in digital videos. The proposed method is composed of two parts: feature extraction and abnormal point detection. In the feature extraction, quotients of correlation coefficients among sequential local binary pattern coded frames are calculated. In the abnormal point detection, insertion and deletion localization is achieved by using Tchebyshev inequality twice followed by abnormal points detection based on decision-thresholding. Experimental results show that our method has high detection accuracy and low computational complexity.

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