Abstract
With the advent of low-cost and high-resolution digital cameras and sophisticated editing software, it is becoming increasingly easier to tamper with the digital image. A common form of manipulation is to combine parts of the image fragment into another different image to remove objects from the image. Inspired by the digital image correlation concept, we exploit the peak of cross-correlation function to automatically detect the splicing artifacts in any fragment of an image. We show the efficacy of the proposed scheme on revealing the source of spliced regions. We make the first concrete technique towards appropriate tools which are necessary for rendering digital forgeries.
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References
Farid, H.: Detecting Digital Forgeries Using Bispectral Analysis. Technical Report AIM-1657, AI Lab, Massachusetts Institute of Technology (1999)
Ng, T.T., Chang, S.F., Lin, C.Y., Sun, Q.: Passive-blind Image Forensics. In: Zeng, W., Yu, H., Lin, C.Y. (eds.) Multimedia Security Technologies for Digital Rights, ch. 15, pp. 383–412. Academic Press, Missouri (2006)
Popescu, A.C., Farid, H.: Exposing Digital Forgeries by Detecting Traces of Re-sampling. IEEE Transaction on Signal Processing 53(2), 758–767 (2005)
Prasad, S., Ramakrishnan, K.R.: On Resampling Detection and its Application to Detect Image Tampering. In: IEEE International Conference on Multimedia and Expo, ICME (2006)
Ye, S., Sun, Q., Chang, E.C.: Detecting Digital Image Forgeries by Measuring Inconsistencies of Blocking Artifact. In: IEEE International Conference on Multimedia and Expo, ICME (2007)
Pan, X., Lyu, S.: Region Duplication Detection using Image Feature Matching. IEEE Transaction on Information Forensics and Security 5(4), 857–867 (2010)
Farid, H., Lyu, S.: Higher-order Wavelet Statistics and their Application to Digital Forensics. In: IEEE Workshop on Statistical Analysis in Computer Vision (in Conjunction with CVPR) (2003)
Ng, T.T., Chang, S.F., Sun, Q.: Blind Detection of Photomontage using Higher Order Statistics. In: IEEE International Symposium on Circuits and Systems, vol. 5, pp. 688–691 (2004)
Avcibas, I., Bayram, S., Memon, N., Sankur, B., Ramkumar, M.: A Classifier Design for Detecting Image Manipulations. In: IEEE International Conference on Image Processing, ICIP (2004)
Bayram, S., Avcibas, I., Sankur, B., Memon, N.: Image Manipulation Detection. Journal of Electronic Imaging 15(4), 041102 (2006)
Chen, W., Shi, Y.Q., Su, W.: Image Splicing Detection using 2-D Phase Congruency and Statistical Moments of Characteristic Function. In: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, vol. 6505, art. No. 65050R. SPIE, Washington (2007)
Dong, J., Wang, W., Tan, T., Shi, Y.Q.: Run-Length and Edge Statistics Based Approach for Image Splicing Detection. In: Kim, H.-J., Katzenbeisser, S., Ho, A.T.S. (eds.) IWDW 2008. LNCS, vol. 5450, pp. 76–87. Springer, Heidelberg (2009)
Sutthiwan, P., Shi, Y.Q., Zhao, H., Ng, T.T., Su, W.: Markovian Rake Transform for Digital Image Tampering Detection. In: Shi, Y.Q., Emmanuel, S., Kankanhalli, M.S., Chang, S.-F., Radhakrishnan, R., Ma, F., Zhao, L. (eds.) Transactions on DHMS VI. LNCS, vol. 6730, pp. 1–17. Springer, Heidelberg (2011)
Wang, W., Farid, H.: Exposing digital forgeries in video by detecting duplication. In: Proceeding ACM Workshop on MMSec, Dallas, TX (2007)
Ng, T.T.: Statistical and Geometric Methods for Passive-blind Image Forensics. Ph.D. Dissertation, Columbia University (2007)
Liu, J., Iskander, M.: Digital Image Correlation. In: Iskander, M. (ed.) Modeling with Transparent Soils, SSGG, pp. 137–164. Springer, Heidelberg (2010)
Ye, S.M., Sun, Q.B., Chang, E.C.: Error resilient content-based image authentication over wireless channel. In: IEEE Int. Symp. Circuits and Systems, ISCAS, Kobe, Japan, pp. 2707–2710 (2005)
Ng, T.T., Chang, S., Sun, Q.: A data set of authentic and spliced image blocks. In: ADVENT Technical Report 203-2004-3. Columbia University (June 2004), http://www.ee.columbia.edu/trustfoto
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Ciptasari, R.W., Rhee, KH., Sakurai, K. (2012). An Image Splicing Detection Based on Interpolation Analysis. In: Lin, W., et al. Advances in Multimedia Information Processing – PCM 2012. PCM 2012. Lecture Notes in Computer Science, vol 7674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34778-8_36
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DOI: https://doi.org/10.1007/978-3-642-34778-8_36
Publisher Name: Springer, Berlin, Heidelberg
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