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.

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