Abstract

Diabetic retinopathy (damage to the retina) is a disease caused by complications of diabetes, which can eventually lead to blindness. It is an ocular manifestation of diabetes, a systemic disease, which affects up to 80 percent of all patients who have had diabetes for 10 years or more. Despite these intimidating statistics, research indicates that at least 90% of these new cases could be reduced if there was proper and vigilant treatment and monitoring of the patient eyes. The longer a person has diabetes, the higher his or her chances of developing diabetic retinopathy. In this paper, we introduced a new method for eye fundus image analysis, based on exudate segmentation. The proposed algorithm detects the existence of exudates and measures its distribution. In this paper, we classified images of eye fundus into no-exudate or have exudates. This initial classification helps physicians to initiate a treatment process for infected patients. The algorithm is tested using DIARETDB0. The results proved the reliability and robustness of algorithm.

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