Retinal Identification Based on Density Clustering and Fuzzy Logic and Connecting This information to Electronic Health Record Authors

This paper aims at identification of individuals using the retinal image that the extraction of blood vessels based on density classification and identification is carried out according to the Fuzzy logic and then according to the performed operations of individual’s electronic health record. For this purpose, a new algorithm was presented for extraction of specific characteristics of retina based on image analysis and statistic calculations. Extraction of eye blood vessels is carried out based on adaptive filters. Our proposed method in comparison to previous methods which merely have carried out the identification through individually comparison of retina has a higher accuracy and speed. This distinction in the identification accuracy and speed was used in the type of classification and Fuzzy rules. In this paper, we will cluster the image noise at the first stage and at the end of clustering, two classes of noise and the original image will remain. This clustering will be done using the density method of Density-Based Clustering. Then we will extract the eye vessels using adaptive filters. After identifying classes and eye vessels extraction, we will identify the image of the retina under experiment based on the five-stage Fuzzy logic and rules and extract the individual’s file