Exposing Original and Duplicated Regions Using SIFT Features and Resampling Traces

  • David Vázquez-Padín
  • Fernando Pérez-González
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7128)


A common type of digital image forgery is the duplication of a region in the same image to conceal something in a captured scene. The detection of region duplication forgeries has been recently addressed using methods based on SIFT features that provide points of the regions involved in the tampering and also the parameters of the geometric transformation between both regions. However, considering this output, there is not yet any information about which of the regions are originals and which are the duplicated ones. A reliable image forensic analysis must provide this information. In this paper, we propose to use a resampling-based method to provide an accurate way to distinguish the original and the tampered regions by analizing the resampling factor of each area. Comparative results are presented to evaluate the performance of the combination of both methods.


Image forensics region duplication resampling estimation SIFT 


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  1. 1.
    Sencar, H.T., Memon, N.: Overview of state-of-the-art in digital image forensics. Part of Indian Statistical Institute Platinum Jubilee Monograph series titled Statistical Science and Interdisciplinary Research. World Scientific Press (2008)Google Scholar
  2. 2.
    Amerini, I., Ballan, L., Caldelli, R., Del Bimbo, A., Serra, G.: Geometric Tampering Estimation by Means of a SIFT-based Forensic Analysis. In: Proceedings of 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1702–1705 (2010)Google Scholar
  3. 3.
    Pan, X., Lyu, S.: Region duplication detection using image feature matching. IEEE Transactions on Information Forensics and Security 5(4), 857–867 (2010)CrossRefGoogle Scholar
  4. 4.
    Vázquez-Padín, D., Mosquera, C., Pérez-González, F.: Two-dimensional statistical test for the presence of almost cyclostationarity on images. In: Proceedings of 2010 17th IEEE International Conference on Image Processing (ICIP), pp. 1745–1748 (2010)Google Scholar
  5. 5.
    Mahdian, B., Saic, S.: Blind authentication using periodic properties of interpolation. IEEE Transactions on Information Forensics and Security 3(3), 529–538 (2008)CrossRefGoogle Scholar
  6. 6.
    Kirchner, M., Gloe, T.: On resampling detection in re-compressed images. In: Proceedings of 2009 First IEEE International Workshop on Information Forensics and Security (WIFS), pp. 21–25 (2009)Google Scholar
  7. 7.
    Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91–110 (2004)CrossRefGoogle Scholar
  8. 8.
    SIFT Keypoint Detector,
  9. 9.

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • David Vázquez-Padín
    • 1
  • Fernando Pérez-González
    • 1
    • 2
    • 3
  1. 1.Signal Theory and Communications Dept.University of VigoVigoSpain
  2. 2.GRADIANTVigoSpain
  3. 3.Dept. of Electrical and Computer EngineeringUniversity of New MexicoUSA

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