Retina recognition is the most stable and reliable biometric system due to its stability, uniqueness and non-replicable nature of vascular pattern. On the other hand, the complexity of vascular pattern in diseased retina makes the extraction of blood vessels very hard, which majorally effects the recognition rate. The main aim of this paper is to design a robust retinal recognition system with reduced computational complexity and to explore novel retinal features. This paper presents two different approaches for retinal recognition; one is vascular-based feature extraction with an improved vessel segmentation algorithm and second is non-vascular based feature extraction. Vascular-based method uses vessel properties of retinal images and aims to improve the efficiency of retinal recognition system. Whereas, non-vascular based method intends to analyze non-vessel properties of retinal images in order to reduce time complexity. The proposed system is assessed on two local and three public databases. 
Person identification using vascular and non-vascular retinal features