Intensity features based classification of hard exudates in retinal images

A major cause of blindness is diabetic retinopathy, which is found in the people who suffer from diabetes, which can be detected through a screening process. Hard exudates are one of the signs of diabetic retinopathy, which caused due to breakdown of retinal blood vessels. This paper presents a method for classification of hard exudates using 6-Dimensional intensity based features. The exudates and non-exudates (background) classification is performed using the Euclidean distance classifier. The proposed method is tested against publicly available databases such as DIARETDB1, e-ophtha EX, MESSIDOR. The proposed algorithm demonstrates maximum subject level accuracy of 96.92% on DIARETDB1.