  Among many biometrics such as face, iris, fingerprint and others, periocular
region has the advantages over other biometrics because it is non-intrusive and
serves as a balance between iris or eye region (very stringent, small area) and
the whole face region (very relaxed large area). Research have shown that this
is the region which does not get affected much because of various poses, aging,
expression, facial changes and other artifacts, which otherwise would change to
a large variation. Active research has been carried out on this topic since
past few years due to its obvious advantages over face and iris biometrics in
unconstrained and uncooperative scenarios. Many researchers have explored
periocular biometrics involving both visible (VIS) and infra-red (IR) spectrum
images. For a system to work for 24/7 (such as in surveillance scenarios), the
registration process may depend on the day time VIS periocular images (or any
mug shot image) and the testing or recognition process may occur in the night
time involving only IR periocular images. This gives rise to a challenging
research problem called the cross-spectral matching of images where VIS images
are used for registration or as gallery images and IR images are used for
testing or recognition process and vice versa. After intensive research of more
than two decades on face and iris biometrics in cross-spectral domain, a number
of researchers have now focused their work on matching heterogeneous
(cross-spectral) periocular images. Though a number of surveys have been made
on existing periocular biometric research, no study has been done on its
cross-spectral aspect. This paper analyses and reviews current state-of-the-art
techniques in cross-spectral periocular recognition including various
methodologies, databases, their protocols and current-state-of-the-art
recognition performances.
