Efficient video frame insertion and deletion detection based on inconsistency of correlations between local binary pattern coded frames

Frame insertion and deletion are common inter-frame forgery in digital videos. In this paper, an efficient method based on quotients of correlation coefficients between local binary patterns (LBPs) coded frames is proposed. This method is composed of two parts: feature extraction and abnormal point detection. In the feature extraction, each frame of a video is coded by LBP. Then, quotients of correlation coefficients among sequential LBP-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. Copyright (c) 2014 John Wiley & Sons, Ltd.