Image Forensic Analysis And Recognition In Copy-Move Using Bag Of Features And Svm

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2019 by IJETT Journal
Volume-67 Issue-5
Year of Publication : 2019
Authors : R.Bharat Kumar , Ch.V.V.S.Srinivas , Abdul Rahaman Shaik
  10.14445/22315381/IJETT-V67I5P201

MLA 

MLA Style: R.Bharat Kumar , Ch.V.V.S.Srinivas , Abdul Rahaman Shaik "Image Forensic Analysis And Recognition In Copy-Move Using Bag Of Features And Svm" International Journal of Engineering Trends and Technology 67.5 (2019): 1-6.

APA Style: R.Bharat Kumar , Ch.V.V.S.Srinivas , Abdul Rahaman Shaik (2019). Image Forensic Analysis And Recognition In Copy-Move Using Bag Of Features And Svm International Journal of Engineering Trends and Technology, 67(5), 1-6.

Abstract
Digital image forgery is a developing issue as the picture could be effectively controlled. Various image processing tools can be forged from digital image forgery. Forging process consists of recompression technique which will erase the traces of existed un-compressed images. The recompressed images are obtained in this proposed system by the process of detection of traces. So the proposed forgery image detection approach will produce periodicity analysis with the double compression effect in spatial domain. Experimental results exhibit that the proposed procedure is performed well on the discovery of fraud limitation.

Reference
[1] Experimental results show that the proposed scheme can achieve much better detection results.
[2] M. M. Yeung, “Digital watermarking,” Commun. ACM, vol. 41, p.30, 1998.
[3] J. Fridrich, “Methods for tamper detection in digital images,” in Proceedings of Multimedia and Security Workshop at ACM Multimedia „99, pp. 19-23, 1999.
[4] Shinfeng D. Lin and Yu-Hsun Huang, “An Integrated Watermarking Technique With Tamper Detection and Recovery,” International Journal of Innovative Computing, Information and Control, Vol. 5, Num. 11, Nov. 2009, SCI.
[5] A.C. Popescu and H. Farid, “Exposing digital forgeries by detecting traces of re-sampling,” IEEE Transactions on Signal Processing, vol. 53, no. 2, pp. 758- 767, 2005.
[6] A.C. Popescu and H. Farid, “Exposing digital forgeries in color filter array interpolated images,” IEEE Transactions on Signal Processing, 2005.
[7] J. Lukas, J. Fridrich, and M. Goljan, “Detecting digital image forgeries using sensor pattern noise,” in Proceedings of the SPIE, vol. 6072, pp. 60720Y, 2006.
[8] A. C. Popescu and H. Farid, “Exposing Digital Forgeries by Detecting Duplicated Image Regions,” Technical Report, TR2004- 515, Dartmouth College, Computer Science, 2004.
[9] H. L. Huang, W. Q. Guo, and Y. Zhang, “Detection of copy-move forgery in digital images using SIFT algorithm,” in IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, pp. 272-276, 2008.
[10] I. Amerini, L. Ballan, R. Caldelli, A.
[11] D. Bimbo, and G. Serra, “Geometric tampering estimation by means of a SIFT-based forensic analysis,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. 1702- 1705, 2010.
[12] X. Pan and S. Lyu, “Detecting image region duplication using SIFT features,” IEEE Transactions on Information Forensics and Security, vol. 5, no. 4, pp.857-867, 2010.
[13] E. Ardizzone, A. Bruno and G. Mazzola, “Detecting Multiple Copies in Tampered Image,” in Proceedings of IEEE 17th International Conference on Image Processing, pp. 2117-2120, 2010.
[14] Z. C. Lin, J. F. He, X. Tang, and
[15] C. K. Tang; “Fast, Automatic and FineGrained Tampered JPEG Image Detection via DCT Coefficient Analysis,” Pattern Recognition, Vol. 42, Issue 11, pp. 2492-2501, Nov. 2009.
[16] H. Bay, A. Ess, T. Tuytelaars, and
[17] L. Van Gool, “SURF: Speeded-up robust features,” International Journal on Computer Vision and Image Understanding, vol. 110, no. 3, pp. 346-359, 2008.

Keywords
Digital image forensics; passive forgery detection, discrete cosine transform (DCT), Speeded up Robust Features (SURF), spatial and colour rich model (SCRM)