“Exposing Photo Manipulation With Inconsistent Reflections” by O’Brien and Farid

  • ©James F. O'Brien and Hany Farid

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    Exposing Photo Manipulation With Inconsistent Reflections

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Abstract:


    The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. In this article we describe a new forensic technique that focuses on geometric inconsistencies that arise when fake reflections are inserted into a photograph or when a photograph containing reflections is manipulated. This analysis employs basic rules of reflective geometry and linear perspective projection, makes minimal assumptions about the scene geometry, and only requires the user to identify corresponding points on an object and its reflection. The analysis is also insensitive to common image editing operations such as resampling, color manipulations, and lossy compression. We demonstrate this technique with both visually plausible forgeries of our own creation and commercially produced forgeries.

References:


    Adelson, E. H. 2000. The New Cognitive Neurosciences, 2nd Ed. MIT Press, Chapter Lightness Perception and Lightness Illusions, 339–351.Google Scholar
    Avidan, S. and Shamir, A. 2007. Seam carving for content-aware image resizing. ACM Trans. Graph. 26, 3. Google ScholarDigital Library
    Bertamini, M., latto, R., and Spooner, A. 2003. The Venus effect: people’s understanding of mirror reflections in paintings. Perception 32, 593–599.Google ScholarCross Ref
    Bertamini, M. and Parks, T. E. 2005. On what people know about images on mirrors. Cognition 98, 85–104.Google ScholarCross Ref
    Bravo, M. and Farid, H. 2001. Texture perception on folded surfaces. Perception 30, 7, 819–832.Google ScholarCross Ref
    Caprile, B. and Torre, V. 1990. Using vanishing points for camera calibration. Int. J. Comput. Vision 4, 127–140. Google ScholarDigital Library
    Cavanagh, P., Chao, J., and Wang, D. 2008. Reflections in art. Spat. Vis. 21, 3-5, 261–270.Google Scholar
    Croucher, C. J., Bertamini, M., and Hecht, H. 2002. Naive optics: Understanding the geometry of mirror reflections. J. Exper. Psychl. Hum. Percept. Perform. 28, 3, 546–562.Google ScholarCross Ref
    Farid, H. 2009. A survey of image forgery detection. IEEE Signal Process. Mag. 2, 26, 16–25.Google ScholarCross Ref
    Farid, H. and Bravo, M. 2010. Image forensic analyses that elude the human visual system. In Proceedings of the SPIE Symposium on Electronic Imaging.Google Scholar
    Fridrich, J. 2009. Digital image forensic using sensor noise. IEEE Signal Process. Mag. 26, 2, 26–37.Google ScholarCross Ref
    Fridrich, J., Soukal, D., and Lukas, J. 2003. Detection of copy move forgery in digital images. In Proceedings of the Digital Forensic Research Workshop.Google Scholar
    Garry, M. and Gerrie, M. 2005. When photographs create false memories. Current Direct. Psychol. Sci. 14, 326–330.Google ScholarCross Ref
    Garry, M. and Wade, K. 2005. Actually, a picture is worth less than 45 words: Narratives produce more false memories than photographs. Psychonom. Bull. Rev. 12, 359–366.Google ScholarCross Ref
    Gloe, T., Winkler, A., and Borowka, K. 2010. Efficient estimation and large-scale evaluation of lateral chromatic aberration for digital image forensics. In Proceedings of the SPIE Conference on Media Forensics and Security.Google Scholar
    Grabler, F., Agrawala, M., Li, W., Dontcheva, M., and Igarashi, T. 2009. Generating photo manipulation tutorials by demonstration. ACM Trans. Graph. 28, 3. Google ScholarDigital Library
    Hartley, R. and Zisserman, A. 2004. Multiple View Geometry in Computer Vision. Cambridge University Press. Google ScholarDigital Library
    Hays, J. and Efros, A. A. 2007. Scene completion using millions of photographs. ACM Trans. Graph. 26, 3. Google ScholarDigital Library
    Johnson, M. and Farid, H. 2007a. Detecting photographic composites of people. In Proceedings of the 6th International Workshop on Digital Watermarking. Google ScholarDigital Library
    Johnson, M. K. and Farid, H. 2005. Exposing digital forgeries by detecting inconsistencies in lighting. In Proceedings of the ACM Multimedia and Security Workshop. 1–10. Google ScholarDigital Library
    Johnson, M. K. and Farid, H. 2006. Exposing digital forgeries through chromatic aberration. In Proceedings of the ACM Multimedia and Security Workshop. 48–55. Google ScholarDigital Library
    Johnson, M. K. and Farid, H. 2007b. Exposing digital forgeries in complex lighting environments. IEEE Trans. Inf. Forens. Secur. 3, 2, 450–461. Google ScholarDigital Library
    Kee, E. and Farid, H. 2010. Exposing digital forgeries from 3-D lighting environments. In Proceedings of the Workshop on Information Forensics and Security.Google Scholar
    Kelby, S. 2008. The Digital Photography Book. Peachpit Press. Google ScholarDigital Library
    Kirchner, M. 2010. Efficient estimation of CFA pattern configuration in digital camera images. In Proceedings of the SPIE Conference on Media Forensics and Security.Google ScholarCross Ref
    Kirchner, M. and Gloe, T. 2009. On resampling detection in re-compressed images. In Proceedings of the IEEE Workshop on Information Forensics and Security. 21–25.Google Scholar
    Kubovy, M. 1986. The Psychology of Perspective and Renaissance Art. Cambridge University Press.Google Scholar
    Light, K. 2004. Fonda, Kerry and photo fakery. The Washington Post. (2/28, A21).Google Scholar
    Lukas, J., Fridrich, J., and Goljan, M. 2006. Digital camera identification from sensor noise. IEEE Trans. Inf. Forens. Secur. 1, 2, 205–214. Google ScholarDigital Library
    Montague, J. 2010. Basic Perspective Drawing. 5th Ed. John Wiley and Sons.Google Scholar
    Ng, T.-T. and Chang, S.-F. 2004. A model for image splicing. In Proceedings of the IEEE International Conference on Image Processing.Google Scholar
    Ostrovsky, Y., Cavanagh, P., and Sinha, P. 2005. Perceiving illumination inconsistencies in scenes. Perception 34, 1301–1314.Google ScholarCross Ref
    Pan, X. and Lyu, S. 2010. Detecting image region duplication using SIFT features. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing. 1706–1709.Google Scholar
    Peters, J. W. 2010. On The Economist’s cover, only a part of the picture. The New York Times. (7/5).Google Scholar
    Popescu, A. C. and Farid, H. 2004. Exposing digital forgeries by detecting duplicated image regions. Tech. rep. TR2004-515, Department of Computer Science, Dartmouth College.Google Scholar
    Popescu, A. C. and Farid, H. 2005a. Exposing digital forgeries by detecting traces of re-sampling. IEEE Trans. Signal Process. 53, 2, 758–767. Google ScholarDigital Library
    Popescu, A. C. and Farid, H. 2005b. Exposing digital forgeries in color filter array interpolated images. IEEE Trans. Signal Process. 53, 10, 3948–3959. Google ScholarDigital Library
    Potter, M. 1976. Short-term conceptual memory for pictures. J. Exper. Psychol. Hum. Learn. Memory 2, 509–522.Google ScholarCross Ref
    Riess, C. and Angelopoulou, E. 2010. Scene illumination as an indicator of image manipulation. In Proceedings of the International Workshop on Information Hiding. Google ScholarDigital Library
    Ritschel, T., Okabe, M., Thormählen, T., and Seidel, H.-P. 2009. Interactive reflection editing. In Proceedings of ACM SIGGRAPH Asia. 129:1–129:7. Google ScholarDigital Library
    Sacchi, D., Agnoli, F., and Loftus, E. 2007. Doctored photos and memory for public events. Appl. Cogn. Psychol. 21, 1005–1022.Google ScholarCross Ref
    Shelbourne, T. 2007. Photoshop CS3 Photo Effects Cookbook. O’Rilly. Google ScholarDigital Library
    Sinha, P., Balas, B., Ostrovsky, Y., and Russell, R. 2006. Face recognition by humans: 19 results all computer vision researchers should know about. Proc. IEEE 94, 11, 1948–1962.Google ScholarCross Ref
    Sunkavalli, K., Johnson, M. K., Matusik, W., and Pfister, H. 2010. Multi-scale image harmonization. ACM Trans. Graph. 29, 4. Google ScholarDigital Library
    Vishwanath, D., Girshick, A., and Banks, M. 2005. Why pictures look right when viewed from the wrong place. Nature Neurosci. 10, 8, 1401–1410.Google ScholarCross Ref
    Wade, K., Garry, M., Read, J., and Lindsay, D. 2002. A picture is worth a thousand lies. Psychonom. Bull. Rev. 9, 597–603.Google ScholarCross Ref
    Wade, N. 2005. Clone scientist relied on peers and Korean pride. The New York Times (12/25).Google Scholar
    Westheimer, G. and McKee, S. 1975. Visual acuity in the presence of retinal-image motion. J. Optic. Soc. Amer. 65, 847–850.Google ScholarCross Ref


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