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Screening System for Early Detection of Diabetic Retinopathy

Diabetic retinopathy is one of the serious eye disease that can cause blindness and vision loss. An automated system for the early detection of DR can save a patient vision and can also help the ophthalmologist in screening of DR which contains different types of lesion, i.e., micro aneurysms and haemorrhages. Accordind by WHO, by 2030 DR wll be fifth leading cause of visual impairement and fourth leading cause of vision loss in the world. The need for automatic detection of DR at an early stage is the objective of the project. In this paper, we have proposed an superpixel algorithm to detect the various stages of DR lesions like exudates, haemorrhages and micro aneurysms. We have used skin locus technique for segmentation and support vector machine (SVM) Classifier with linear kernel to classify the stages of DR. The detection of stages of DR was found to be good and we obtained a classification accuracy of 97%.