bibliography on detection of image/video tampering

Overview of tampering detection

1.         C. Amsberry, Alterations of photos raise host of legal, ethical issues," The Wall Street Journal, Jan 1989.

2.         Siwei Lyu, Natural Image statistics for digital image forensics, Phd Thesis, Dartmouth university.

3.         A. Popescu and H. Farid, Statistical tools for digital forensics, In Proceeding of 6th International Workshop on Information Hiding 2004.

4.         Tian-Tson Ng, Shih-Fu Chang, Ching-Yung Lin, Qibin Sun. Passive-blind Image Forensics. In Multimedia Security Technologies for Digital Rights, W. Zeng, H. Yu, and Ching-Yung Lin (eds.), Elsvier, 2006.

5.         Hany Farid, Creating and Detecting Doctored and Virtual Images: Implications to The Child Pornography Prevention Act, TR2004-518, Dartmouth College, Computer Science.

Data set

6.         T.-T. Ng, S.-F. Chang, J. Hsu, and M. Pepeljugoski, Columbia photographic images and photorealistic computer graphics dataset, Columbia University, ADVENT Technical Report 205-2004-5, Feb 2005. [Online]. Available: http://www.ee.columbia.edu/trustfoto.

7.         Calphoto, A database of photos of plants, animals, habitats and other natural history subjects, University of Berkeley, 2000. [Online]. Available: http://elib.cs.berkeley.edu/photos/.

8.         T.-T. Ng and S.-F. Chang, A data set of authentic and spliced image blocks, Columbia University, ADVENT Technical Report 203-2004-3, June 2004. [Online]. Available: http://www.ee.columbia.edu/trustfoto.

9.         www.worth1000.com.

10.     www.fakeorfoto.com.

Tampering detection by checking inconsistency of camera characteristics

Based on camera response function

11.    Z. Lin, R. Wang, X. Tang, and H.-Y. Shum. Detecting doctored image using camera response normality and consistency. In Proceedings of CVPR 2005, pp. 1087-1092.

12.   T.-T. Ng and S.-F. Chang, A model for image splicing, in IEEE International Conference on Image Processing, 2004.

13.    T.-T. Ng, S.-F. Chang, and Q. Sun. Blind detection of photomontage using higher order statistics. In Proceeding of IEEE International Symposium on Circuits and Systems, 2004.

14.    S. Lin, J. Gu, S. Yamazaki, and H.-Y. Shum. Radiometric calibration from a single image. in Proceeding of CVPR 2004, vol. 2, pp. 938-945.

15.    S. Lin and L. Zhang, Determining the radiometric response function from a single grayscale image," in Proceeding of CVPR 2005, vol. 2, pp. 66-73.

16.    T.-T. Ng, S.-F. Chang, and M.-P. Tsui, Camera response function estimation from a single-channel image using differential invariants," in review, 2005.

Based on camera CFA pattern

17.     A. Popescu and H. Farid. Exposing digital forgeries in color filter array interpolated images," IEEE Transactions on Signal Processing, vol. 53, no. 10, pp. 3948-3959, 2005.

18.    B. E. Bayer. ※Color imaging array,§ US Patent, 3971065, 1976.

19.    R. Ramanath, W. E. Snyder, G. L. Bilbro, and W. A. Sander III. Demosaicking methods for Bayer color arrays. Journal of Electronic Imaging, vol. 11, no. 3, pp. 306每315, July 2002.

Based on camera noise

20.    J. Lukas, J. Fridrich, and M. Goljan. Detecting digital image forgeries using sensor pattern noise," in SPIE Electronic Imaging, Photonics West, January 2006.

21.    H. Farid and A.C. Popescu, Blind Removal of Image Non-Linearities, In Proceeding of ICCV 2001

22.    I. Avcibas, S. Bayram, N. Memon, M. Ramkumar, and B. Sankur. A classifier design for detecting image manipulations," in IEEE International Conference on Image Processing, vol. 4, Singapore, Oct 2004, pp. 2645-2648.

Tampering detection by checking image manipulation

23.    Junfeng He, Zhouchen Lin, Lifeng Wang, and Xiaoou Tang.   Detecting Doctored JPEG Images via DCT Coefficient Analysis, ECCV 2006

24.    W. Wang and H. Farid . Exposing Digital Forgeries in Video by Detecting Double MPEG Compression. ACM Multimedia and Security Workshop, Geneva, Switzerland, 2006

25.    A. Popescu and H. Farid, Exposing digital forgeries by detecting traces of re-sampling. IEEE Transactions on Signal Processing, vol. 52, no. 2, pp. 758-767, 2005.

26.    W. Wang and H. Farid. Exposing Digital Forgeries in Interlaced and De-Interlaced Video. IEEE Transactions on Information Forensics and Security, 2(3):438-449, 2007.

27.    A. Popescu and H. Farid, Exposing digital forgeries by detecting duplicated image regions. Computer Science, Dartmouth College, Tech. Rep. TR2004-515, 2004. [Online]. Available: http://www.cs.dartmouth.edu/?farid/publications/tr04.pdf

28.    W. Wang and H. Farid. Exposing Digital Forgeries in Video by Detecting Duplication. ACM Multimedia and Security Workshop, Dallas, TX, 2007

29.    H. Farid. Digital Video Forensics. American Academy of Forensic Sciences, Washington, DC, 2008.

30.    H. Farid . Exposing Digital Forgeries in Scientific Images. ACM Multimedia and Security Workshop, Geneva, Switzerland, 2006 

Tampering detection by checking inconsistency of scene characteristics

31.     M. Johnson and H. Farid. Exposing digital forgeries by detecting inconsistencies in lighting. in ACM Multimedia and Security Workshop, New York, NY, 2005.

32.    P. Nillius and J.-O. Eklundh. Automatic estimation of the projected light source direction. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001.

33.    D. Mahajan, R. Ramamoorthi, and B. Curless. Spherical harmonic convolution for inverse rendering, BRDF/lighting transfer and image consistency checking. in review, 2005.

34.    A. Pentland. Finding the illuminant direction. Journal of the Optical Society of America, 72(4):448-455, 1982.

35.    J.-M. Pinel, H. Nicolas, and C. L. Bris. Estimation of 2D illuminant direction and shadow segmentation in natural video sequences. In Proceedings of VLBV 2001, pp. 197-202.

36.    M.K. Johnson and H. Farid. Exposing Digital Forgeries Through Specular Highlights on the Eye. 9th International Workshop on Information Hiding, Saint Malo, France, 2007.

37.    M.K. Johnson and H. Farid. Detecting Photographic Composites of People. 6th International Workshop on Digital Watermarking, Guangzhou, China, 2007.

38.     Micah K. Johnson. Lighting and Optical Tools for Image Forensics. Ph.D. Dissertation, Department of Computer Science, Dartmouth College, 2007.

Related topics

Classify computer graphic images from photos

39.    T.-T. Ng, S.-F. Chang, J. Hsu, L. Xie, and M.-P. Tsui. Physics-motivated features for distinguishing photographic images and computer graphics," in ACM Multimedia, Singapore, November 2005.

40.    H. Farid and S. Lyu. Higher-order wavelet statistics and their application to digital forensics, in IEEE Workshop on Statistical Analysis in Computer Vision, Madison, Wisconsin, 2003.

41.    H. Farid. Detecting digital forgeries using bispectral analysis, MIT, MIT AI Memo AIM-1657, 1999. [Online]. Available: ftp://publications.ai.mit.edu/ai-publications/pdf/AIM-1657.pdf

42.    S. Lyu and H. Farid. How realistic is photorealistic. IEEE Transactions on Signal Processing, vol. 53, no. 2, pp. 845-850, February 2005.

43.    A. B. Lee, K. S. Pedersen, and D. Mumford. The nonlinear statistics of high-contrast patches in natural images. International Journal of Computer Vision, vol. 54, no. 1, pp. 83-103, 2003.

44.     A. Srivastava, A. B. Lee, E. P. Simoncelli, and S.-C. Zhu. On advances in statistical modeling of natural images. Journal of Mathematical Imaging and Vision, vol. 18, no. 1, pp. 17-33, 2003.

45.    T. Ianeva, A. de Vries, and H. Rohrig. Detecting cartoons: A case study on automatic video-genre classification. In IEEE International Conference on Multimedia and Expo, vol. 1, 2003, pp. 449-452.

Art authentication

46.     R. Taylor, A. P. Micolich, and D. Jones. Fractal analysis of pollock*s drip paintings. Nature, pp. 399:422, 1999.

47.     Siwei Lyu, Daniel Rockmore, and Hany Farid. A digital technique for art authentication, PNAS, December 7, 2004, vol. 101, no. 49, pp. 17006每17010

Forensic image analysis

48.    Luk芍š J., Fridrich J., and Goljan M.: Determining Digital Image Origin Using Sensor Imperfections, In Proceedings of SPIE Electronic Imaging, Image and Video Communication and Processing 2005, pp. 249每260.

49.    K. Mehdi, H. Sencar, and N. Memon. Blind source camera identification. In IEEE International Conference on Image Processing 2004, vol. 1, pp. 709-712.

50.    A. K. Mikkilineni, P.-J. Chiang, G. N. Ali, G. T.-C. Chiu, J. P. Allebach, and E. J. Delp. Printer identification based on texture features. In proceeding of IS&T International Conference on Digital Printing Technologies, 2004, pp. 306-312.

Information hiding and its detection

51.    S. Lyu and H. Farid. Detecting hidden messages using higher-order statistics and support vector machines. In 5th International Workshop on Information Hiding 2002.

52.    Fridrich J., M. Goljan, D. Hogea, and D. Soukal. Quantitative steganalysis of digital images: Estimating the secret message length. ACM Multimedia Systems Journal, Special issue on Multimedia Security, 9(3):288每302, 2003.

53.    E. A. P. Petitcolas, R. J. Anderson, and M. G. Kuhn. Information hiding - a survey. In Proceedings of the IEEE, 87(7):1062每1078, 1999.

54. I. Venturini. Counteracting oracle attacks. In ACM multimedia and security workshop on Multimedia and security 2004, pp. 187-192.