Review of Techniques for the Detection of Passive Video Forgeries

Authors(2) :-Misbah U. Mulla, Prabhu R. Bevinamarad

Due to the availability of various types of digital cameras and video technology giving rise to multimedia data for communication purpose.Digital videos play an important role in court rooms,in news,defense and for security purpose to ensure their authenticity and integrity is a important task and also a challenge. On the other hand due to advancement of technology and availability of various editing software tools has made the digital video tampering possible allowing it to modify,edit and alter easily,the digital forensics demands effective research in this field to find different techniques to detect the video forgeries.The various techniques are proposed by the researchers for video tampering detection. But passive techniques are based on detecting the forgeries without the need of pre embedded information .This review paper focuses on various passive techniques which are used to detect forgeries in videos.

Authors and Affiliations

Misbah U. Mulla
Department of Computer Science and Engineering, B.L.D.E.A'S Dr.P.G.Halakatti College of Engineering and Technology, Vijayapur, Karnataka, India
Prabhu R. Bevinamarad
Department of Computer Science and Engineering, B.L.D.E.A'S Dr.P.G.Halakatti College of Engineering and Technology, Vijayapur, Karnataka, India

Video Forgeries, Passive Techniques.

  1. Sowmya K.N and H.R. Chennamma, “A Survey on Video Forgery Detection”,in International Journal of Computer Engineering and Applications, Volume IX,  pp. 17-27 ,     February 2015.
  2. Shashank Sharma and Sunita V Dhavale,“A Review of Passive Forensic Techniques for Detection of Copy-Move Attacks on Digital Videos”,in IEEE 3rd International Conference on Advanced Computing and Communication Systems (ICACCS ),2016.
  3. Shobhita Saxena,A.V.Subramanyam and Hareesh Ravi, “Video Inpainting Detection and Localization Using Inconsistencies in Optical Flow”,in 2016 IEEE Region 10 Conference (TENCON) — Proceedings of the International Conference, pp .1361-1365,2016.
  4. Lichao Su ,Tianqiang Huang and Jianmei Yang, “A video forgery detection algorithm based on compressive sensing” , Springer Science and Business Media New York  ,pp. 6641-6656 , 2014.
  5. Dijana Tralic, Sonja Grgic and Branka Zovko-Cihlar, “Video Frame Copy-Move Forgery Detection Based on Cellular Automata and Local Binary Patterns”, in IEEE X International Symposium on Telecommunications (BIHTEL), October 2014.
  6. Jianmei Yang ,Tianqiang Huang and  Lichao Su  “Using similarity analysis to detect frame duplication forgery in videos”, Springer Science and Business Media New York ,pp. 1793-1811,2014.
  7. A.V. Subramanyam and Sabu Emmanuel, “Pixel Estimation Based Video Forgery Detection”,in IEEE 2013 ICASSP ,pp.3038-3042,2013.
  8. Juan Chao ,Xinghao Jiang and Tanfeng Sun, “A Novel Video Inter-frame Forgery Model Detection Scheme Based on Optical Flow Consistency”,Springer-Verlag Berlin Heidelberg , pp. 267–281, 2013.
  9. Kesav Kancherla and Srinivas Mukkamala, “Novel Blind Video Forgery Detection Using Markov Models on Motion Residue”, Springer-Verlag Berlin Heidelberg, pp. 308–315, 2012.
  10. A.V. Subramanyam and Sabu Emmanuel, “Video forgery detection using hogfeatures and compression properties” ,in IEEE  International Conference on Multimedia signal processing. pp.89 - 94 , 2012.
  11. Julian Goodwin and Girija Chetty, “Blind Video Tamper Detection Based on Fusion of Source Features”,in IEEE International Conference on Digital Image Computing: Techniques and Applications,pp. 608-613,2011.
  12. Yuting Su, Jing Zhang and Jie Liu, “Exposing Digital Video Forgery by Detecting Motion-compensated Edge Artifact”, in IEEE International Conference on Computational Intelligence and Software Engineering(CiSE), 2009.
  13. Michihiro Kobayashi, Takahiro Okabe, and Yoichi Sato, “Detecting Video Forgeries Based on Noise Characteristics”,Springer-Verlag Berlin Heidelberg , pp. 306–317, 2009.
  14. Chih-Chung Hsu , Tzu-Yi Hung, Chia-Wen Lin, Chiou-Ting Hsu,“Video Forgery Detection Using Correlation of Noise Residue”, in IEEE 10th workshop on multimedia signal processing , pp .170-174,2008.
  15. Weihong Wang and Hany Farid, “Exposing Digital Forgeries in Interlaced and Deinterlaced Video”, IEEE Transactions on Information Forensics and Security, Vol. 2, NO. 3, pp .438-449 ,September  2007.
  16. S. V. Porter ,M. Mirmehdi  and B. T. Thomas, “Video Cut Detection using Frequency Domain Correlation”,in 15th International Conference on Pattern Recognition, pp .409-412, 2000.

Publication Details

Published in : Volume 2 | Issue 3 | May-June 2017
Date of Publication : 2017-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 199-203
Manuscript Number : CSEIT172315
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Misbah U. Mulla, Prabhu R. Bevinamarad, "Review of Techniques for the Detection of Passive Video Forgeries", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 3, pp.199-203, May-June-2017.
Journal URL : http://ijsrcseit.com/CSEIT172315

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