The Impact of Print-and-Scan in Heterogeneous Morph Evaluation Scenarios
Richard E. Neddo Zander W. Blasingame Chen Liu
Face morphing attacks present an emerging threat to the face recognition
system. On top of that, printing and scanning the morphed images could obscure
the artifacts generated during the morphing process, which makes morphed image
detection even harder. In this work, we investigate the impact that printing
and scanning has on morphing attacks through a series of heterogeneous tests.
Our experiments show that we can increase the possibility of a false match by
up to 5.64% for DiM and 16.00% for StyleGAN2 when providing an image that has
been printed and scanned, regardless it is morphed or bona fide, to a Face
Recognition (FR) system. Likewise, using Frechet Inception Distance (FID)
metric, strictly print-scanned morph attacks performed on average 9.185%
stronger than non-print-scanned digital morphs.