Detection of resampled images: Performance analysis and practical challenges
Francesca Uccheddu, Alessia De Rosa, Alessandro Piva, Mauro Barni · Use Siena air (University of Siena) · 2010
The assessment of the practical performance of forensic methods for the detection of resampling operations on digital images is a difficult task requiring a careful experimental analysis. Unfortunately, the experimental analysis reported in multimedia forensics papers is often statistically insufficient, or at least not usable to predict the performance of the proposed systems at scales needed for practical deployment. This paper attempts to move a first step to fill this gap in a twofold way. First of all a proper experimental framework is proposed to analyze the performance of resampling detectors. Then the suggested methodology is applied to evaluate the performance of two of the most significant resampling detectors proposed so far, providing a deeper-than-usual analysis of their behavior under different working conditions.