Temel Kavramlar
Print-and-scan processing can significantly increase the effectiveness of face morphing attacks against face recognition systems, regardless of whether the input image is a morphed or bona fide face.
Özet
The paper investigates the impact of print-and-scan processing on the effectiveness of face morphing attacks in heterogeneous evaluation scenarios. Key highlights:
- Print-and-scan processing can increase the false match rate of face recognition systems by up to 5.64% for DiM morphs and 16.00% for StyleGAN2 morphs, compared to digital-only morphs.
- Using the Fréchet Inception Distance (FID) metric, strictly print-scanned morph attacks performed on average 9.185% stronger than non-print-scanned digital morphs in terms of visual fidelity.
- The paper examines four attack configurations that combine digital and print-scanned bona fide and morphed images, highlighting the vulnerabilities of face recognition systems to heterogeneous data.
- Experiments were conducted on the FRLL, FERET, and FRGC datasets using three face recognition systems: ArcFace, ElasticFace, and AdaFace.
- The results show that print-and-scan processing can effectively mask morphing artifacts, making it harder for face recognition systems to detect morphed images, especially when the reference data is also print-scanned.
İstatistikler
Print-and-scan processing can increase the false match rate by up to 5.64% for DiM morphs and 16.00% for StyleGAN2 morphs.
Strictly print-scanned morph attacks performed on average 9.185% stronger than non-print-scanned digital morphs in terms of visual fidelity.
Alıntılar
"Print-and-scan processing can effectively mask morphing artifacts, making it harder for face recognition systems to detect morphed images, especially when the reference data is also print-scanned."
"The presence of inconsistent data when comparing potentially morphed images against bona fide images is an area lacking research."