Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Exposing digital forgeries in video by detecting double MPEG compression
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Space-Time Completion of Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exposing digital forgeries in video by detecting duplication
Proceedings of the 9th workshop on Multimedia & security
Exemplar-based video inpainting without ghost shadow artifacts by maintaining temporal continuity
IEEE Transactions on Circuits and Systems for Video Technology
Exposing Digital Forgeries in Interlaced and Deinterlaced Video
IEEE Transactions on Information Forensics and Security - Part 1
Video Inpainting Under Constrained Camera Motion
IEEE Transactions on Image Processing
Screenshot identification using combing artifact from interlaced video
Proceedings of the 12th ACM workshop on Multimedia and security
Novel blind video forgery detection using markov models on motion residue
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part III
Detecting removed object from video with stationary background
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
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In the digital multimedia era, it is increasingly important to ensure the integrity and authenticity of the vast volumes of video data. A novel approach is proposed for detecting video forgery based on ghost shadow artifact in this paper. Ghost shadow artifact is usually introduced when moving objects are removed by video inpainting. In our approach, ghost shadow artifact is accurately detected by inconsistencies of the moving foreground segmented from the video frames and the moving track obtained from the accumulative frame differences, thus video forgery is exposed. Experiments show that our approach achieves promising results in video forgery detection.