  Presentation Attack Detection (PAD) has been extensively studied,
particularly in the visible spectrum. With the advancement of sensing
technology beyond the visible range, multispectral imaging has gained
significant attention in this direction. We present PAD based on multispectral
images constructed for eight different presentation artifacts resulted from
three different artifact species. In this work, we introduce Face Presentation
Attack Multispectral (FPAMS) database to demonstrate the significance of
employing multispectral imaging. The goal of this work is to study
complementary information that can be combined in two different ways (image
fusion and score fusion) from multispectral imaging to improve the face PAD.
The experimental evaluation results present an extensive qualitative analysis
of 61650 sample multispectral images collected for bonafide and artifacts. The
PAD based on the score fusion and image fusion method presents superior
performance, demonstrating the significance of employing multispectral imaging
to detect presentation artifacts.
