Fast and reliable resampling detection by spectral analysis of fixed linear predictor residue
Proceedings of the 10th ACM workshop on Multimedia and security
The 'Dresden Image Database' for benchmarking digital image forensics
Proceedings of the 2010 ACM Symposium on Applied Computing
Digital camera identification from sensor pattern noise
IEEE Transactions on Information Forensics and Security
Determining Image Origin and Integrity Using Sensor Noise
IEEE Transactions on Information Forensics and Security
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Although sensor noise is generally known as a very reliable means to uniquely identify digital cameras, care has to be taken with respect to camera model characteristics that may cause false accusations. While earlier reports focused on so-called linear patterns with a regular grid structure, also distortions due to geometric corrections of radial lens distortion have recently gained interest. Here, we report observations from a case study with the 'Dresden Image Database' that revealed further artefacts. We found diagonal line artefacts in Nikon CoolPix S710 sensor noise, as well as non-trivial dependencies between sensor noise, exposure time (FujiFilm J50) and focal length (Casio EX-Z150). At slower shutter speeds, original J50 images exhibit a slight horizontal shift, whereas EX-Z150 images exhibit irregular geometric distortions, which depend on the focal length and which become visible in the p-map of state-of-the-art resampling detectors. The observed artefacts may provide valuable clues for camera model identification, but also call for particular attention when creating reference noise patterns for applications that require low false negative rates.