Person Identification using Local and Structural Features of Retina Vessels

Retina-based identification system is a stable and reliable biometric system that does not have problems like oblivion, being exposed, lost, and forgery. In this paper, a new method with high precision performance is presented which, unlike other retina-based methods, is resistant to rotation and displacement of the vessels. The system consists of three main stages of pre-processing, extraction of features and matching of features. Extraction of vessels is carried out using mixed continuous wavelet transform method. At the extraction stage, using local pattern detection operator, the characteristic of the special points of the vessels, such as the number of branches, the smallest angle and the type of points (branch and intersection), is identified. In the matching of features step, the number of special matching points and the degree of similarity of the topology of the graph resulting from the connection of the feature points of the input image and the reference image are calculated and ultimately the identity of the individual will be detected. The proposed method has been implemented on the DRIVE, VARIA, DIARET and STARE databases, which it’s accuracy was100% , 99.81%, 99.7% and 100% respectively.