Chunhui Feng
ABSTRACT
Detection of frame deletion is of great significance in the field of video forensics. Several approaches have been presented through analyzing the side effect caused by frame deletion. However, most of the current approaches can detect the existence of frame deletion but not the exact location of it. In this paper, we present a method which can directly locate the frame deletion point. Through the analysis of the distinguishing fluctuation feature of motion residual caused by frame deletion compared to interference frames and ordinary video content jitter in tampered video sequence, an algorithm based on the total motion residual of video frame is proposed to detect the frame deletion point. Moreover, an initiative processing procedure for frame motion residual and an adaptive threshold detector are introduced so that the robustness of the detection can be markedly improved. Experimental results show that the proposed algorithm is effective in generalized scenarios such as different encoding settings, rapid or slow motion sequences and multiple group of picture deletion. It also has a high performance that the true positive rate reaches 90% and the false alarm rate is less than 0.8%.
- P. Bestagini, M. Fontani, S. Milani et al. An Overview on Video Forensics. 2012 Proceedings of the 20th European Signal Processing Conference, Bucharest, Romania, August 27 - 31, 2012.Google Scholar
- J. Chao, X. Jiang, and T. Sun. A Novel Video Inter-frame Forgery Model Detection Scheme Based on Optical Flow Consistency. Digital Forensics and Watermarking, LNCS 7809: 267--281, 2013. Google ScholarDigital Library
- I. J. Cox, M. L. Miller, and J. A. Bloom. Digital Watermarking. San Francisco, CA: Morgan Kaufmann, 2002. Google ScholarDigital Library
- W. Chen and Y.Q. Shi. Detection of Double MPEG Compression Based on First Digit Statistics. Digital Watermarking, 2009, 5450: 16--30. Google ScholarDigital Library
- R. C. Gonzalez and R. E. Woods. Digital Image Processing. (2nd ed.) Prentice-Hall, New Jersey (2002): 793 Google ScholarDigital Library
- S. Katzenbeisser and F. A. P. Petitcolas. Information Hiding Techniques for Steganography and Digital Watermarking. Norwood, MA: Artec House, 2000. Google ScholarDigital Library
- W. Luo, Z. Qu, J. Huang, and G. Qiu. A Novel Method for Detecting Cropped and Recompressed Image Block. IEEE International Conference on Acoustics, Speech and Signal Processing, 2: II-217--II-220.Google Scholar
- J. Lee, I. Shin, and H. Park. Adaptive Intra-Frame Assignment and Bit-Rate Estimation for Variable GOP Length in H.264. IEEE Transactions on Circuits and Systems for Video Technology, 16(10): 1271--1279, 2006. Google ScholarDigital Library
- J. Ostermann, J. Bormans, P. List, et al. Video Coding with H.264/AVC: Tools, Performance, and Complexity. IEEE Transactions on Circuits and Systems for Video Technology, 15(7): 7--28, 2005.Google Scholar
- A. C. Popescu and H. Farid. Statistical Tools for Digital Forensics. Information Hiding, LNCS 3200: 128--147, 2005. Google ScholarDigital Library
- D. V. Padín, M. Fontani, T. Bianchi, et al. Detection of video double encoding with GOP size estimation. The IEEE International Workshop on Information Forensics and Security, 2--5, 2012.Google Scholar
- M. C. Stamm, W. S. Lin, and K. J. R. Liu. Temporal Forensics and Anti-Forensics for Motion Compensated Video. IEEE Transactions on Information Forensics and Security, 7(4): 1315--1329, 2012.Google ScholarDigital Library
- A. Swaminathan, M. Wu, and K. J. R. Liu. Digital Image Forensics via Intrinsic Fingerprints. IEEE Transactions on Information Forensics and Security, 3(1): 101--117, 2008. Google ScholarDigital Library
- Y. Su, J. Zhang, and J. Liu. Exposing Digital Video Forgery by Detecting Motion-compensated Edge Artifacts. International Conference on Computational Intelligence and Software Engineering: 1--4, 2009.Google ScholarCross Ref
- T. Shanableh. Detection of Frame Deletion for Digital Video Forensics. Digital Investigation, 10(4): 350--360, 2013. Google ScholarDigital Library
- W. Wang and H. Farid. Exposing Digital Forgeries in Interlaced and Deinterlaced Video. IEEE Transactions on Information Forensics and Security, 2(3): 438--449, 2007. Google ScholarDigital Library
- W. Wang and Hany Farid. Exposing Digital Forgeries in Video by Detecting Double MPEG Compression. MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security, 2006: 37--47. Google ScholarDigital Library
- Weihong Wang and Hany Farid. Exposing Digital Forgeries in Video by Detecting Duplication. MM&Sec '07 Proceedings of the 9th workshop on Multimedia and security, 2007: 35--42. Google ScholarDigital Library
- W. Wang, H. Farid. Exposing Digital Forgeries in Video by Detecting Double Quantization. MM&Sec '07 Proceedings of the 9th workshop on Multimedia and security, 2009: 39--48. Google ScholarDigital Library
- H.264 / MPEG-4 Part 10 White Paper. Prediction of Intra Macroblocks; Prediction of Inter Macroblocks in P- slices.Google Scholar
- http://en.wikipedia.org/wiki/Frame_rateGoogle Scholar
- http://www.videolan.org/developers/x264.htmlGoogle Scholar
- http://trace.eas.asu.edu/yuv/Google Scholar
Index Terms
- Automatic location of frame deletion point for digital video forensics
Recommendations
An approach to detect video frame deletion under anti-forensics
As a simple yet effective operation, frame deletion is widely used in video forgery. Many video forensic techniques have been developed to detect this manipulation. Some inter-frame continuity based methods are capable to detect frame deletion as well ...
Detecting video frame-rate up-conversion based on periodic properties of edge-intensity
Video frame-rate up-conversion (FRUC) is one of the common temporal-domain operations. From the earlier frame repetition and linear interpolation, FRUC has been developed to motion compensated frame interpolation (MCFI), which effectively overcomes the ...
Exposing frame deletion by detecting abrupt changes in video streams
Many existing methods for frame deletion detection attempt to detect abnormal periodical artifacts in video stream, however, due to a number of reasons, the periodical artifacts can not always be reliably detected. In this paper, we propose a new method ...
Comments