Discriminating multiple JPEG compression using first digit features
The analysis of double-compressed images is a problem largely studied by the multimedia forensics community, as it might be exploited, e.g., for tampering localization or source device identification. In many practical scenarios, e.g. photos uploaded on blogs, on-line albums, and photo sharing Web sites, images might be compressed several times. However, the identification of the number of compression stages applied to an image remains an open issue. This paper proposes a forensic method based on the analysis of the distribution of the first significant digits of DCT coefficients, which is modeled according to Benford's law. The method relies on a set of Support Vector Machine (SVM) classifiers and allows us to accurately identify the number of compression stages applied to an image. Up to four consecutive compression stages were considered in the experimental validation. The proposed approach extends and outperforms the previously published methods aimed at detecting double JPEG compression.