  Recently, concerns regarding potential biases in the underlying algorithms of
many automated systems (including biometrics) have been raised. In this
context, a biased algorithm produces statistically different outcomes for
different groups of individuals based on certain (often protected by
anti-discrimination legislation) attributes such as sex and age. While several
preliminary studies investigating this matter for facial recognition algorithms
do exist, said topic has not yet been addressed for vascular biometric
characteristics. Accordingly, in this paper, several popular types of
recognition algorithms are benchmarked to ascertain the matter for fingervein
recognition. The experimental evaluation suggests lack of bias for the tested
algorithms, although future works with larger datasets are needed to validate
and confirm those preliminary results.
