Research On Digital Video Inter-Frame Forgery Detection Based On Content Continuity

Research on passive forensics of digital video has always been a hot issue in the field of multimedia security.This thesis focuses on digital video inter-frame tamper operations and base on the principle that tamper operation will destroy the principle of the relevance and continuity of the adjacent frames in the content.We detected digital video forgey in time domain,such as frame insertion,frame deletion,and copy-move operation.We proposed two methods to detect forgery video:1.Video tamper detection method based on nonnegative tensor factorization.First,the algorithm uses discrete cosine transform to quickly extract video features and quantize them so that each video can be described by a three-dimensional tensor.Then Tucker decomposition of the video tensor is used to extract the time dimension matrix information representing the video features.We use the principle that the video adjacent frames are highly similar to perform the calculation of the correlation coefficient of the video adjacent frames and locate the tampered positions.Experiments show that the algorithm can effectively detect the tampering in the video time domain,and the detection speed is faster than the other similar algorithms.2.A multi-channel approach through fusion of audio for detecting video inter-frame forgery.The forgery operation of digital video in the temporal domain is often accompanied by the synchronization of the audio channel operation.In this thesis,we proposed a fusion of audio forensics detection methods for video inter-frame forgery.First,the audio channel of the video is extracted and discrete wavelet packet decomposition and analysis of singularity points of audio signals are used to locate the forged singularity points.Next,features of each frame of the video are extracted with the perceptual hash and used to calculate the similarity between consecutive frames,to locate the forgery position in the video frame sequence.We fused the results of the audio channel and the video frame sequence channel.The QDCT feature is used to further fine detect the suspected forgery location.Our method can position replication source locations for copy-move forgery.Experiments show that our method has higher accuracy and better performance in comparison with similar methods,especially on the delete forgery operation.