Abstract

The vein structure in the sclera, the white and opaque outer protective covering of the eye, is anecdotally
stable over time and unique to each person. As a result, it is well suited for use as a biometric for human
identification. Sclera recognition poses several challenges: the vein structure moves and deforms with the
movement of the eye and its surrounding tissues; images of sclera patterns are often defocused and/or
saturated; and, most importantly, the vein structure in the sclera is multi-layered and has complex non-linear
deformation. Here proposed a new method for sclera recognition, a line descriptor along with feature
extraction, registration, and matching method that is scale, orientation, and deformation invariant, and can
mitigate the multi-layered deformation effects and tolerate segmentation error.