On the detectability of local resampling in digital images

In Ref. 15, we took a critical view on the reliability of forensic techniques as tools to generate evidence of authenticity for digital images and presented targeted attacks against the state-of-the-art resampling detector by Popescu and Farid. We demonstrated that a correct detection of manipulations can be impeded by resampling with geometric distortion. However, we constrained our experiments to global image transformations. In a more realistic scenario, most forgeries will make use of local resampling operations, e.g., when pasting a beforehand scaled or rotated object. In this paper, we investigate the detectability of local resampling without and with geometric distortion and study the influence of the size both of the tampered and the analyzed image region. Although the detector might fail to reveal the characteristic periodic resampling artifacts, a forensic investigator can benefit from the generally increased correlation in resampled image regions. We present an adapted targeted attack, which allows for an increased degree of undetectability in the case of local resampling.