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In the context of Computer Aided Diagnosis system for diabetic retinopathy,we present a novel method for detection of exudates and their classificationfor disease severity prediction. The method is based on Gaussian scale spacebased interest map and mathematical morphology. It makes use of support vectormachine for classification and location information of the optic disc and themacula region for severity prediction. It can efficiently handle luminancevariation and it is suitable for varied sized exudates. The method has beenprobed in publicly available DIARETDB1V2 and e-ophthaEX databases. For exudatedetection the proposed method achieved a sensitivity of 96.54% and predictionof 98.35% in DIARETDB1V2 database.

A Gaussian Scale Space Approach For Exudates Detection, Classification And Severity Prediction