  Lossy face image compression can degrade the image quality and the utility
for the purpose of face recognition. This work investigates the effect of lossy
image compression on a state-of-the-art face recognition model, and on multiple
face image quality assessment models. The analysis is conducted over a range of
specific image target sizes. Four compression types are considered, namely
JPEG, JPEG 2000, downscaled PNG, and notably the new JPEG XL format. Frontal
color images from the ColorFERET database were used in a Region Of Interest
(ROI) variant and a portrait variant. We primarily conclude that JPEG XL allows
for superior mean and worst case face recognition performance especially at
lower target sizes, below approximately 5kB for the ROI variant, while there
appears to be no critical advantage among the compression types at higher
target sizes. Quality assessments from modern models correlate well overall
with the compression effect on face recognition performance.
