The Impact of Print-and-Scan in Heterogeneous Morph Evaluation Scenarios
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.
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