Design and develop a computer aided design for automatic exudates detection for diabetic retinopathy screening

Diabetic retinopathy is a severe and widely spread eye disease which can lead to blindness. one of the main symptoms for vision loss is exudates and it could be prevented by applying an early screening process. in the existing systems,a fuzzy c-means clustering technique is used for detecting the exudates for analyzation. the main objective of this paper is,to improve the efficiency of the exudates detection in diabetic retinopathy images. to do this,a three stage – [ts] approach is introduced for detecting and extracting the exudates automatically from the retinal images for screening the diabetic retinopathy. ts functions on the image in three levels such as pre-processing the image,enhancing the image and detecting the exudates accurately. after successful detection,the detected exudates are classified using glcm method for finding the accuracy. the ts approach is experimented using matlab software and the performance evaluation can be proved by comparing the results with the existing approach’s result and with the hand-drawn ground truths images from the expert ophthalmologist. © school of engineering,taylor’s university,all rights reserved.