Robust Face Morphing Attack Detection Using Fusion of Multiple Features and Classification Techniques. (arXiv:2305.03264v1 [cs.CV])

Face Recognition System (FRS) are shown to be vulnerable to morphed images of
newborns. Detecting morphing attacks stemming from face images of newborn is
important to avoid unwanted consequences, both for security and society. In
this paper, we present a new reference-based/Differential Morphing Attack
Detection (MAD) method to detect newborn morphing images using Wavelet
Scattering Network (WSN). We propose a two-layer WSN with 250 $\times$ 250
pixels and six rotations of wavelets per layer, resulting in 577 paths. The
proposed …

arxiv attacks classification detection face face recognition features fusion images multiple paper recognition reference security society stemming vulnerable