Abstract
Copy-move forgery is one of the most common types of video forgeries. To detect such forgery, a new algorithm based on structural similarity is proposed. In this algorithm, we extend structural similarity to measure the similarity between two frames of a video. Since the value of similarity between duplicated frames is higher than that between the normal inter-frames, a temporal similarity measurement strategy between short sub-sequences is put forward to detect copy-move forgery. In addition, we can obtain an accurate forgery localization. Extensive experimental results evaluated on 15 videos captured by the digital camera and mobile camera in stationary and moving mode show that the precision of this algorithm can reach 99.7 % which is higher than a previous relevant study.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Milani S, Fontani M, Bestagini P et al (2012) An overview on video forensics. APSIPA Trans Signal Inf Process 1:e2. doi:10.1017/ATSIP.2012.2
Wang W, Farid H (2006) Exposing digital forgeries in video by detecting double MPEG compression. In: Proceedings of the 8th workshop on multimedia and security. doi: 10.1145/1161366.1161375
Wang W, Farid H (2009) Exposing digital forgeries in video by detecting double quantization. In: Proceedings of the 11th ACM workshop on multimedia and security. doi: 10.1145/1597817.1597826
Luo W, Wu M, Huang J (2008) MPEG recompression detection based on block artifacts. In: Proceedings of the SPIE on security, forensics, steganography and watermarking of multimedia imaging. doi:10.1117/12.767112
Su Y, Zhang J, Liu J (2009) Exposing digital video forgery by detecting motion-compensated edge artifact. In: Proceedings of international conference on computational intelligence and software engineering. doi: 10.1109/CISE.2009.5366884
Dong Q, Yang G, Zhu N (2012) A MCEA based passive forensics scheme for detecting frame-based video tampering. Digit Invest 9(2):151–159
Qin Y, Sun G, Zhang X (2009) Exposing digital forgeries in video via motion vectors. J Comput Res Dev. 46(Suppl.):227–233 (in Chinese)
Huang T, Chen Z (2011) Digital video forgeries detection based on bidirectional motion vectors. J Shandong Univ (Engineering Science) 41(4):13–19 (in Chinese)
Stamm MC, Liu KJR (2011). Anti-forensics for frame deletion/addition in MPEG video. In: Proceedings of 2011 IEEE international conference on acoustics, speech and signal processing (ICASSP). doi: 10.1109/ICASSP.2017.5946872
Stamm MC, Lin WS, Liu KJR (2012) Temporal forensics and anti-Forensics for motion compensated video. IEEE Trans Inf Forensics Secur 7(4):1315–1329
Weihong W, Hany F (2007) Exposing digital forgeries in video by detecting duplication. In: Proceedings of the 9th workshop on multimedia and security. doi: 10.1145/1288869.1288876
Chih-Chung H, Tzu-Yi H, Lin C-W, Chiou-Ting H (2008) Video forgery detection using correlation of noise residue. In: Proceedings of 2008 IEEE 10th workshop on multimedia signal processing. doi: 10.1109/MMSP.2008.4665069
Kobayashi M, Okabe T, Sato Y (2010) Detecting forgery from static-scene video based on inconsistency in noise level functions. IEEE Trans Inf Forensics Secur 5(4):883–892
Subramanyam AV, Emmanuel S (2012) Video forgery detection using HOG features and compression properties. In: Proceedings of 2012 IEEE 14th international workshop on multimedia signal processing (MMSP). doi: 10.1109/MMSP.2012.6343421
Lin G-S, Chang J-F (2012) Detection of frame duplication forgery in videos based on spatial and temporal analysis. Int J Pattern Recognit Artif Intell 26(7):1–18
Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612
Acknowledgments
This work was supported by the National Natural Science Foundation of China (Grant No. 61070062), Industry-university Cooperation Major Projects in Fujian Province (Grant No. 2012H6006), Program for New Century Excellent Talents in University in Fujian Province(Grant No. JAI1038).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, F., Huang, T. (2014). Video Copy-Move Forgery Detection and Localization Based on Structural Similarity. In: Farag, A., Yang, J., Jiao, F. (eds) Proceedings of the 3rd International Conference on Multimedia Technology (ICMT 2013). Lecture Notes in Electrical Engineering, vol 278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41407-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-41407-7_7
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41406-0
Online ISBN: 978-3-642-41407-7
eBook Packages: EngineeringEngineering (R0)