Diabetic retinopathy is an eye disease and causes vision loss to the people who are suffering longer from the diabetes. Exudates, bright and red lesions are identified in the diabetic retinal eye. Automatic detection and localization of macular edema is a challenging issue since exudates have non uniform illumination and are low contrasted. Proposed algorithm to detect macular edema encompasses Simple Linear Iterative Clustering, Fisher linear discriminant and Support vector machine classifer. Optic Disc extraction prior to exudates extraction is also introduced. Performance of the proposed detection algorithm is tested on easily available databases: Diaretdb1, Messidor and E_optha Ex. Proposed method shows an accuracy of 97.81%, specificity 98.65 and Sensitivity 82.71%.

Keywords : Macular Edema, Exudates, Superpixel, Simple Linear Iterative Clustering, Fisher’s Linear Discriminant, Support Vector Machine.