Detection of exudates and feature extraction of retinal images using fuzzy clustering method

Diabetic retinopathy (DR) is the micro vascular changes that cause detectable changes in the optic disc. This paper aims at the detection of retinal exudates and other features such as blood vessels and optic disc from fundus image. The two methods are implemented for the detection of exudates they are morphological method and FCM clustering method. Contrast limited adaptive histogram equalization (CLACHE) is used to extract the green component in the image. In blood vessel extraction, blood vessels are extracted by top hat transformation followed by connected component analysis. The optic disc centre is found using Circular Hough Transform (CHT) and propagation through radii method is employed and the entire optic disc region is blackened and removed. Exudates detection is the important characteristics of diabetic retinopathy and its varies depends upon the severity of the DR. The FCM method used to detect exudates. The overall sensitivity, specificity and accuracy are calculated and 98% accuracy obtained.