COUNTERING ANTI-FORENSICS OF IMAGE RESAMPLING

Image resampling leaves behind periodical artifacts which are used as fingerprints for the forensics. A knowledgeable anti-forensic method erases such artifacts by irregular sampling. We observe that the irregular sampling followed by interpolation causes changes in local linear correlations, and propose a novel method to detect the anti-forensic method of resampling via partial autocorrelation coefficients. Experimental results on a large set of images show that the proposed method could effectively detect the anti-forensics of resampling with a low dimensional feature set.