Moving Targets CopyMove Forgery Detection in Video Sequences

Journal of Shanghai Jiaotong University ›› 2015, Vol. 49 ›› Issue (02): 196-201.

• Automation Technique, Computer Technology • Previous Articles Next Articles

Moving Targets CopyMove Forgery Detection in Video Sequences

ZHANG Luboa,SUN Tanfenga,b,c,JIANG Xinghaoa,b,c

(a. School of Electronic Information and Electrical Engineering; b. National Engineering Laboratory on Information Content Analysis Techniques; c. Shanghai Key Laboratory of Administration Technologies for Information Security, Shanghai Jiaotong University, Shanghai 200240, China)

Received:2014-06-11 Online:2015-02-28 Published:2015-02-28

Abstract

Abstract:

Abstract： In this paper, a novel technique to detect moving targets copy-move forgery in video sequences based on LK optical flow and the pre-screening mechanism of moving targets was proposed. The proposed scheme is a coarse-to-fine approach and composed of moving targets detection and tracking, candidate motion sequences selection, and spatial matching. In the pre-processing round, the visual background extractor (ViBe) mechanism and Kalman filter were used to detect and tracking moving objects. To screen duplicated candidates in the temporal domain, the optical flow features in each motion sequences were obtained using the Lucas_Kanade algorithm and calculate their correlation. To evaluate the similarity of image content, the scale invariant feature transform (SIFT) algorithm was used to measure spatial correlation of each corresponding frame between the motion sequences. The experimental results show that the proposed scheme can detect moving targets copy-move forgery well in homologous video.
Key words：

Key words: video tampering detection, moving objects detection and tracking, optical flow algorithm, scale invariant feature, digital video forensics

CLC Number:

TP 391

ZHANG Luboa,SUN Tanfenga,b,c,JIANG Xinghaoa,b,c. Moving Targets CopyMove Forgery Detection in Video Sequences[J]. Journal of Shanghai Jiaotong University, 2015, 49(02): 196-201.

References

［1］Milani S, Fontani M, Bestagini P, et al. An overview on video forensics［J］. APSIPA Transactions on Signal and Information Processing, 2012, 1(1): 118.

［2］Wang W, Farid H. Exposing digital forgeries in video by detecting double MPEG compression ［C］∥Proceedings of the 8th Workshop on Multimedia and Security. New York, USA:ACM, 2006:3747.

［3］Wang W, Farid H. Exposing digital forgeries in video by detecting double quantization ［C］∥Proceedings of the 11th ACM Workshop on Multimedia and Security. New York, USA: ACM, 2009:3948.

［4］Wang W, FARID H. Exposing digital forgeries in video by detecting duplication ［C］∥International Multimedia Conference on Proceeding of the 9th Workshop on Multimedia and Security. Dallas, Texas, USA:ACM, 2007: 3542.

［5］Chao J, Jiang X H, Sun T F. A new video interframe tampering detection method based on optical flow consistency ［C］∥The 11th International Workshop on Digitalforensics and Watermarking. Shanghai: Springer, 2012: 2527.

［6］Stamm M C, Lin W S K, Liu J R. Temporal forensics and antiforensics for motion compensated video ［J］. IEEE Transaction on Information Forensics and Security, 2012, 7(4): 13151329.

［7］李富贵，黄添强，苏立超, 等.融合多特征的异源视频复制粘贴篡改检测［J］.山东大学学报(工学版），2013，43(4): 3238.

LI Fugui, HUANG Tianqiang, SU Lichao, et al. Heterologous video copymove forgery detection by fusing multiple features［J］. Journal of Shandong University (Engineering Science), 2013, 43(4): 3238.

［8］Bestagini P, Milani S, Tagliasacchi M, et al, Local tampering detection in video sequences［C］∥2013 IEEE 15th International Workshop on Multimedia Signal Processing (MMSP). Pula, Italy:IEEE, 2013:488493.

［9］Subramanyam A V, Emmanuel S. Video forgery detection using HOG features and compression properties［C］∥14th IEEE International Workshop on Multimedia Signal Processing (MMSP). Banff, Canada:IEEE, 2012:8994.

［10］Barnich O, Van Droogenbroeck M. ViBe: A universal background subtraction algorithm for video sequences ［J］. IEEE Transactions on Image Processing, 2011, 20(6):17091724.

［11］Welch G, Bishop G.An introduction to the Kalman filter［C］∥SIGGRAPH 2001. Los Angeles, CA: ACM, 2001: 1217.

［12］Lucas B D, Kanade T. An iterative image registration technique with anapplication to stereo vision［C］∥IJCAI. San Francisco, CA USA: Publisher Morgan Kaufmann Publishers Inc, 1981:674679.

［13］Qadir G,Yahaya S, Ho A T S. Surrey university library forforensic analysis (SULFA) of video content ［C］∥IET Conference on Image Processing (IPR 2012). London:IET, 2012: 16.

Moving Targets CopyMove Forgery Detection in Video Sequences

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