Filtering normal retinal images for diabetic retinopathy screening using multiple classifiers

Diabetic retinopathy is a complication of diabetes and early detection is essential for effective treatment. In this paper, a novel technique for the separation of normal and abnormal retinal images is described. Various features are extracted from local sub images and then fed through multiple classifiers to categorise them into interim classes followed by a reasoning process to give a more reliable and robust result. This is then followed by a global analysis to decide the normality of the whole image.