Design and Implementation of Inspection Model for knowledge Patterns Classification in Diabetic Retinal Images

Diabetes is one of the major health issues. In diabetes patient one serious problem experience is the Diabetic Retinopathy (DR) and visual deficiency and is vascular disease of retina. Hence prediction of DR from patient eye retina becomes wry crucial at early stage to cure. We focuses on presenting an empirical method in this research to collect required data and then developing several models to predict the chance of diabetic retinopathy. Here we use diabetic eye retina image dataset as input for prediction and evaluation. There are many techniques and algorithms that help to diagnose DR in retinal fundus images. We utilized some data mining techniques such as Support vector machine (SVM), naive bayes and Local binary pattern (LBP) to extract image features and analyze image dataset.