Statistical fusion of multiple cues for image tampering detection

Conference Record - Asilomar Conference on Signals, Systems and Computers

Volumn , Issue , 2008, Pages 1386-1390

  Hsu, Yu Feng ^a   Chang, Shih Fu ^a  

^a Department of Earth and Environmental Sciences   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERA RESPONSE FUNCTIONS; IMAGE FORENSICS; IMAGE TAMPERING; MODEL PARAMETERS; NATURAL IMAGES; RANDOM FIELDS; SYSTEMATIC EVALUATION; TAMPERING DETECTION;

SIGNAL DETECTION;

DETECTORS;

EID: 70349678692     PISSN: 10586393     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACSSC.2008.5074646     Document Type: Conference Paper

References (14)

1. M.K. Johnson and H. Farid, "Exposing digital forgeries by detecting inconsistencies in lighting," in ACM Multimedia and Security Workshop, 2005.
2. A.C. Popescu and H. Farid, "Exposing digital forgeries in color filter array interpolated images," IEEE Transactions on Signal Processing, vol. 53, no. 10, 2005.
3. A. Swaminathan, M. Wu, and K.J.R. Liu, "Component forensics of digital cameras: a non-intrusive approach," in Conference on Information Sciences and Systems, 2006.
4. J. Lukáš, J. Fridrich, and M. Goljan, "Detecting digital image forgeries using sensor pattern noise," Proceedings of the SPIE, vol. 6072, 2006.
5. Z. Lin, R. Wang, X. Tang, and H.-Y. Shum, "Detecting doctored images using camera response normality and consistency," in International Conference on Computer Vision and Pattern Recognition, 2005.
6. Y.-F. Hsu and S.-F. Chang, "Detecting image splicing using geometry invariants and camera characteristics consistency," in International Conference on Multimedia and Expo, 2006.
7. Y.-F. Hsu and S.-F. Chang, "Image splicing detection using camera response function consistency and automatic segmentation," in International Conference on Multimedia and Expo, 2007.
8. J. He, Z. Lin, L. Wang, and X. Tang, "Detecting doctored jpeg images via dct coefficient analysis," in ECCV (3), 2006.
9. S. Kumar and M. Hebert, "Discriminative random fields," International Journal of Computer Vision, vol. 68, no. 2, 2006.
10. T.-T. Ng, S.-F. Chang, and M.-P. Tsui, "Using geometry invariants for camera response function estimation," in IEEE Conference on Computer Vision and Pattern Recognition, 2007.
11. K. P. Murphy, Y. Weiss, and M. I. Jordan, "Loopy belief propagation for approximate inference: An empirical study," in Uncertainty in Artificial Intelligence, 1999.
12. Y.Weiss, "Comparing the mean field method and belief propagation for approximate inference in mrfs," in Saad and Opper, editors, Advanced Mean Field Methods, MIT Press, 2001.
13. M. I. Jordan, "Why the logistic function? a tutorial discussion on probabilities and neural networks," Tech. Rep., Computational Cognitive Science 9503, Massachusetts Institute of Technology, 1995.
14. S. V. N. Vishwanathan, N. N. Schraudolph, M. W. Schmidt, and K. P. Murphy, "Accelerated training of conditional random fields with stochastic gradient methods," in International Conference on Machine Learning. 2006, ACM Press.