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