Fast Forgery Detection with the Intrinsic Resampling Properties

Cheng-Chang Lien, Cheng-Lun Shih, Chih-Hsun Chou

.

DOI: 10.4236/jis.2010.11002                

Abstract

With the rapid progress of the image processing software, the image forgery can leave no visual clues on the tampered regions and make us unable to authenticate the image. In general, the image forgery technologies often utilizes the scaling, rotation or skewing operations to tamper some regions in the image, in which the resampling and interpolation processes are often demanded. By observing the detectable periodic distribution properties generated from the resampling and interpolation processes, we propose a novel method based on the intrinsic properties of resampling scheme to detect the tampered regions. The proposed method applies the pre-calculated resampling weighting table to detect the periodic properties of prediction error distribution. The experimental results show that the proposed method outperforms the conventional methods in terms of efficiency and accuracy.

Keywords

Image Forgery, Resampling, Forgery Detection, Intrinsic Properties of Resampling

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	R. B. Wolfgang and E. J. Delp, “A Watermark for Digital Image,” Proceedings of the International Conference on Image Processing, Vol. 3, 1996, pp. 219-222.
[2]	R. B. Wolfgang, C. I. Podilchuk and E. J. Delp, “Percep-tual Watermarks for Digital Images and Video,” Pro-ceedings of the IEEE, Special Issue on Identification and Protection of Multimedia Information, Vol. 87, No. 7, 1999, pp. 1108-1126.
[3]	M. Wu and B. Liu, “Watermarking for Image Authenti-cation,” IEEE International Conference on Image Processing, Vol. 2, 1998, pp. 437-441.
[4]	M. Yeung and F. Mintzer, “An Invisible Watermarking Technique for Image Verification,” Proceedings of the International Conference on Image Processing, Vol. 1, 1997, pp. 680-683.
[5]	J. Fridrich, D. Soukal and J. Luká?, “Detection of Copy-Move Forgery in Digital Images,” Proceedings of the Digital Forensic Research Workshop, Cleveland, 2003.
[6]	L. Zhou, D. Wang, Y. Guo and J. Zhang, “Blue Detection of Digital Forgery Using Mathematical Morphology,” Technical Report, KES AMSTA, Springer-Verlag, Berlin, Heidelberg, 2007, pp. 990-998.
[7]	A. C. Popescu and H. Farid, “Exposing Digital Forgeries by Detecting Traces of Resampling,” IEEE Transactions on Signal Processing, Vol. 53, No. 2, 2005, pp. 758-767.
[8]	A. C. Popescu and H. Farid, “Exposing Digital Forgeries in Color Filter Array Interpolated Images,” IEEE Trans-actions on Signal Processing, Vol. 53, No. 10, 2005, pp. 3948-3959.
[9]	M. Kirchner, “Fast and Reliable Resampling Detection by Spectral Analysis of Fixed Linear Predictor Residue,” MM & Sec’08, Proceedings of the Multimedia and Security Workshop, 2008, pp. 11-20.
[10]	S. Prasad and K. Ramakrishnan, “On Resampling Detec-tion and its Application to Detect Image Tampering,” Proceedings of the 2006 IEEE International Conference on Multimedia and EXPO, 2006, pp. 1325-1328.
[11]	B. Mahdian and S. Saic, “Blind Authentication Using Periodic Properties of Interpolation,” IEEE Transactions on Information Forensics and Security, Vol. 3, No. 3, 2008, pp. 529-538.
[12]	B. Mahdian and S. Saic, “Detection of Resampling Sup-plemented with Noise Inconsistencies Analysis for Image Forensics,” International Conference on Computational Sciences and its Applications, Vol. 81, No. 4, 2008, pp. 546-556.
[13]	J. Luká?, J. Fridrich and M. Goljan, “Detecting Digital Image Forgeries Using Sensor Pattern Noise,” Proceed-ings of the SPIE Conference on Security, Steganography and Watermarking of Multimedia Contents, Vol. 6072, 2006, pp. 362-372.
[14]	J. Luká?, J. Fridrich and M. Goljan, “Digital Camera Identification from Sensor Pattern Noise,” IEEE Trans-actions on Information Security and Forensics, Vol. 1, No. 2, 2006, pp. 205-214.
[15]	M. K. Johnson and H. Farid, “Exposing Digital Forgeries in Complex Lighting Environments,” IEEE Transactions on Information Forensics and Security, Vol. 2, No. 4, 2007, pp. 450-461.
[16]	S. Ye, Q. Sun and E. Chang, “Detecting Digital Image Forgeries by Measuring Inconsistencies of Blocking Ar-tifact,” IEEE International Conference on Multimedia and Expo, 2007, pp. 12-15.
[17]	M. C. Stamm and K. J. R. Liu, “Forensic Detection of Image Tampering Using Intrinsic Statistical Fingerprints in Histograms,” Proceedings of the APSIPA Annual Summit and Conference, Sapporo, 2009.