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The possibility of carrying out a meaningful forensics analysis on printedand scanned images plays a major role in many applications. First of all,printed documents are often associated with criminal activities, such asterrorist plans, child pornography pictures, and even fake packages.Additionally, printing and scanning can be used to hide the traces of imagemanipulation or the synthetic nature of images, since the artifacts commonlyfound in manipulated and synthetic images are gone after the images are printedand scanned. A problem hindering research in this area is the lack of largescale reference datasets to be used for algorithm development and benchmarking.Motivated by this issue, we present a new dataset composed of a large number ofsynthetic and natural printed face images. To highlight the difficultiesassociated with the analysis of the images of the dataset, we carried out anextensive set of experiments comparing several printer attribution methods. Wealso verified that state-of-the-art methods to distinguish natural andsynthetic face images fail when applied to print and scanned images. Weenvision that the availability of the new dataset and the preliminaryexperiments we carried out will motivate and facilitate further research inthis area.

VIPPrint: A Large Scale Dataset of Printed and Scanned Images for Synthetic Face Images Detection and Source Linking