Abstract
To create convincing forged images, manipulated images or parts of them are usually exposed to some geometric operations which require a resampling step. Therefore, detecting traces of resampling became an important approach in the field of image forensics. In this paper, we revisit existing techniques for resampling detection and design some targeted attacks in order to assess their reliability. We show that the combination of multiple resampling and hybrid median filtering works well for hiding traces of resampling. Moreover, we propose an improved technique for detecting resampling using image forensic tools. Experimental evaluations show that the proposed technique is good for resampling detection and more robust against some targeted attacks.
Chapter PDF
Similar content being viewed by others
References
Kirchner, M.: Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue. In: Proceedings of the 10th ACM Workshop on Multimedia and Security - MM&Sec 2008 (2008)
Popescu, A.C., Farid, H.: Exposing digital forgeries by detecting traces of resampling. IEEE Transactions on Signal Processing 53, 758–767 (2005)
Prasad, S., Ramakrishnan, K.R.: On resampling detection and its application to detect image tampering. In: ICME (2006)
Gallagher, A.C.: Detection of Linear and Cubic Interpolation in JPEG Compressed Images. In: The 2nd Canadian Conference on Computer and Robot Vision (CRV 2005), pp. 65–72 (2005)
Mahdian, B., Saic, S.: Blind Authentication Using Periodic Properties of Interpolation. IEEE Transactions on Information Forensics and Security 3, 529–538 (2008)
Nguyen, H.C., Katzenbeisser, S.: Performance and robustness analysis for some re-sampling detection techniques in digital images. In: IWDW (2011)
Uccheddu, F., Rosa, A.D., Piva, A., Barni, M.: Detection of resampled images: performance analysis and practical challenges. EURASIP, 1675–1679 (2010)
Kirchner, M., Boehme, R.: Hiding Traces of Resampling in Digital Images. IEEE Transactions on Information Forensics and Security 3, 582–592 (2008)
Wolberg, G.: Digital Image Warping. IEEE Computer Society Press, Los Alamitos (1994)
Garcia, D.: BiomeCardio, http://www.biomecardio.com/matlab/hmf.html
Gonzalez, R., Woods, R., Eddins, S.: Digital image processing using Matlab. Gatesmark Publishing (2009)
Hoilund, C.: The Radon Transform. Aalborg University (2007)
Jafari-Khouzani, K., Soltanian-Zadeh, H.: Rotation-invariant multiresolution texture analysis using radon and wavelet transforms. IEEE Transactions on Image Processing 14, 783–795 (2005)
Schaefer, G., Stich, M.: UCID: an uncompressed color image database. In: Proc. SPIE, Storage and Retrieval Methods and Applications for Multimedia, San Jose, USA, pp. 472–480 (2004)
Voloshynovskiy, S., Herrigel, A., Baumgaertner, N., Pun, T.: A Stochastic Approach to Content Adaptive Digital Image Watermarking. In: Pfitzmann, A. (ed.) IH 1999. LNCS, vol. 1768, pp. 211–236. Springer, Heidelberg (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Nguyen, H.C., Katzenbeisser, S. (2012). Robust Resampling Detection in Digital Images. In: De Decker, B., Chadwick, D.W. (eds) Communications and Multimedia Security. CMS 2012. Lecture Notes in Computer Science, vol 7394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32805-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-32805-3_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32804-6
Online ISBN: 978-3-642-32805-3
eBook Packages: Computer ScienceComputer Science (R0)