Robust Sclera Segmentation for Skin-tone Agnostic Face Image Quality
  Assessment
Wassim Kabbani Christoph Busch Kiran Raja
Face image quality assessment (FIQA) is crucial for obtaining good face
recognition performance. FIQA algorithms should be robust and insensitive to
demographic factors. The eye sclera has a consistent whitish color in all
humans regardless of their age, ethnicity and skin-tone. This work proposes a
robust sclera segmentation method that is suitable for face images in the
enrolment and the border control face recognition scenarios. It shows how the
statistical analysis of the sclera pixels produces features that are invariant
to skin-tone, age and ethnicity and thus can be incorporated into FIQA
algorithms to make them agnostic to demographic factors.