Detection of Linear and Cubic Interpolation in JPEG Compressed Images
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue
Proceedings of the 10th ACM workshop on Multimedia and security
A bibliography on blind methods for identifying image forgery
Image Communication
Exposing digital forgeries by detecting traces of resampling
IEEE Transactions on Signal Processing
Blind Authentication Using Periodic Properties of Interpolation
IEEE Transactions on Information Forensics and Security
Hiding Traces of Resampling in Digital Images
IEEE Transactions on Information Forensics and Security
Robust resampling detection in digital images
CMS'12 Proceedings of the 13th IFIP TC 6/TC 11 international conference on Communications and Multimedia Security
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In order to create convincing forged images, manipulated images are usually exposed to some geometric operations which require a re-sampling step. Therefore, detecting traces of re-sampling became an important approach in the field of image forensics. There are many re-sampling detection techniques described in the literature, but their performance has been often examined with a small dataset. Besides, performance and robustness have been tested under different conditions, so it is difficult to evaluate and compare them. In this paper, we analyze the performance of some selected re-sampling detection techniques by using a common testing framework and a large dataset. We also employ several kinds of image post-processing to defeat the detectors in order to evaluate their robustness and security. We show that the tested techniques obtain the best results when detecting up-sampled images. Unfortunately, most techniques are not secure and they can be defeated on different levels by applying post-processing operations to the forged images.