Abstract
In this paper, a novel approach for exposing digital image tampering based on the theory of spherical harmonic frames is presented. We describe a robust technique for exposing digital forgeries that we utilize the information along a 2D occluding contour and estimate the lighting feature using spherical harmonic frames. Spherical harmonic frames are generated by the rotation along the symmetry axes of a symmetry group. The lighting-based digital forensic technique using spherical harmonic frames inherits the robust property of frames and improve the statistical results compared with spherical harmonic bases. Experimental results performed using spherical harmonic frames prove the robust measurements and discriminability of the complex lighting environments from synthetic data and real data. The application of identifying the tampered images reveals the improvement of our method.
This work is supported by Postdoctoral Science Foundation of China No. 2013M540822, National Natural Science Foundation of China(NSFC, No. 61340046, 60875050, 60675025), National High Technology Research and Development Program of China(863 Program, No. 2006AA04Z247), Scientific and Technical Innovation Commission of Shenzhen Municipality (No. JCYJ20120614152234873, CXC201104210010A, JCYJ20130331144631730, JCYJ20130331144716089)
Chapter PDF
Similar content being viewed by others
References
Farid, H.: A Survey of Image Forgery Detection. IEEE Signal Processing Magazine 26, 16–25 (2009)
Fridrich, J.: Digital Image Forensics. IEEE Signal Processing Magazine 26, 26–37 (2009)
Swaminathan, A., Wu, M., Liu, K.J.R.: Component Forensics: Theory, methodologies, and applications. IEEE Signal Processing Magazine 26, 38–48 (2009)
Ng, T.T., Chang, S.F.: Identifying and Prefiltering Images: Distinguishing between natural photography and photorealistic computer graphics. IEEE Signal Processing Magazine 26, 49–58 (2009)
Rocha, A., Scheirer, W., Boult, T.E., Goldenstein, S.: Vision of the unseen: Current trends and challenges in digital image and video forensics. ACM Computing Surveys (CSUR) 43, 26:1–26:42 (2011)
Johnson, M.K., Farid, H.: Exposing digital forgeries by detecting inconsistencies in lighting. In: Proceedings of the 7th Workshop on Multimedia and Security, pp. 1–10. ACM (2005)
Johnson, M.K., Farid, H.: Exposing digital forgeries through specular highlights on the eye. In: 9th International Workshop on Information Hiding, pp. 311–325 (2007)
Johnson, M.K., Farid, H.: Exposing Digital Forgeries in Complex Lighting Environments. IEEE Transactions on Information Forensics and Security 2, 450–461 (2007)
Stork, D.G., Johnson, M.K.: Lighting analysis of diffusely illuminated tableaus in realist paintings: an application to detecting ‘compositing’ in the portraits of Garth Herrick. In: Electronic Imaging: Media Forensics and Security, pp. 72540L1-8. SPIE (2009)
Farid, H., Kee, E.: Exposing digital forgeries from 3-D lighting environments. In: IEEE International Workshop on Information Forensics and Security (2010)
Zhao, W.Y., Chen, S.L., Zheng, Y., Chen, S.L., Peng, S.L.: Lighting Estimation of a Convex Lambertian Object Using Redundant Spherical Harmonic Frames. Journal of Computer Science and Technology 28, 454–467 (2013)
Nillius, P., Eklundh, J.O.: Automatic estimation of the projected light source direction. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1076–1083. IEEE (2001)
Brunelli, R., Messelodi, S.: Robust estimation of correlation with applications to computer vision. Pattern Recognition, 833–841 (1995)
Ramamoorthi, R., Hanrahan, P.: An efficient representation for irradiance environment maps. In: Proceeding SIGGRAPH 2001 Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, pp. 497–500. ACM (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhao, W., Liu, H. (2015). An Image Forensic Technique Based on 2D Lighting Estimation Using Spherical Harmonic Frames. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 546. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48558-3_33
Download citation
DOI: https://doi.org/10.1007/978-3-662-48558-3_33
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-48557-6
Online ISBN: 978-3-662-48558-3
eBook Packages: Computer ScienceComputer Science (R0)