Automatic Human Recognition Based on the Geometry of Retinal Blood Vessels Network

Retinal biometric is a new methodology that increasingly being used, especially for authentication
cases required high level of persons identification. Retinal recognition deals with very distinct
physical property has, exceptional, very low false acceptance and false rejection rates, and the
features that are determined in the retina of eye are more reliable and stable features than those
found in other biometrics.
This paper presents a new system for personal recognition based on retinal vascular pattern. This
system is capable to compensate the effects of eyes rotation and robust to noise and brightness
variations. The developed system consists of three main stages (i.e., preprocessing, feature
extraction, and matching stage). Preprocessing was used (1) to enhance the retina image, and (2) to
extract the vascular network (i.e., Region of Interest); then a set of discriminating local geometric
features are extracted, it is a set of local average of vascular densities are proposed to define the
vesicular network. Finally, Euclidean distance measure was used in the matching stage. The
proposed system was evaluated on the two publicly available databases: (i) STARE (Structured
Analysis of the Retina) and (ii) DRIVE (Digital Retinal Images for Vessel Extraction). The test results
indicated that the attained recognition accuracy of the proposed method is 100% for both datasets.