Abstract
Abstract: Diabetes is a metabolic condition that causes organ failure, including retinal damage. Diabetic Retinopathy causes blindness by leaking blood vessel fluid into the retina also called as exudates. Thus, there has been a surge of interest in automated methods for detecting diabetic retinopathy using image processing techniques. Using real-time image dataset and image processing techniques, the proposed system is able to detect major retinal abnormalities such as enlarged retinal veins, blood spots, and white-yellow patches that indicate fluid leakage. The system analyses colour retinal images to determine the extent of damage and locate clusters of injured pixels within the region. The technique has a greater detection accuracy of 88%, and it has been demonstrated to be successful in detecting exudates and abnormalities from fundus images. In addition, the system is extremely helpful. To make suggestions for possible treatments based on an examination of the fundus images
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