Paper
27 January 2010 Improving re-sampling detection by adding noise
Author Affiliations +
Proceedings Volume 7541, Media Forensics and Security II; 75410I (2010) https://doi.org/10.1117/12.839086
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
Current image re-sampling detectors can reliably detect re-sampling in JPEG images only up to a Quality Factor (QF) of 95 or higher. At lower QFs, periodic JPEG blocking artifacts interfere with periodic patterns of re-sampling. We add a controlled amount of noise to the image before the re-sampling detection step. Adding noise suppresses the JPEG artifacts while the periodic patterns due to re-sampling are partially retained. JPEG images of QF range 75-90 are considered. Gaussian/Uniform noise in the range of 28-24 dB is added to the image and the images thus formed are passed to the re-sampling detector. The detector outputs are averaged to get a final output from which re-sampling can be detected even at lower QFs. We consider two re-sampling detectors - one proposed by Poposcu and Farid [1], which works well on uncompressed and mildly compressed JPEG images and the other by Gallagher [2], which is robust on JPEG images but can detect only scaled images. For multiple re-sampling operations (rotation, scaling, etc) we show that the order of re-sampling matters. If the final operation is up-scaling, it can still be detected even at very low QFs.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lakshmanan Nataraj, Anindya Sarkar, and B. S. Manjunath "Improving re-sampling detection by adding noise", Proc. SPIE 7541, Media Forensics and Security II, 75410I (27 January 2010); https://doi.org/10.1117/12.839086
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Cited by 16 scholarly publications.
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KEYWORDS
Signal to noise ratio

Sensors

Image compression

Expectation maximization algorithms

Image quality

Raster graphics

Image forensics

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