Diabetic retinopathy (DR) is a common eye condition that affects one-third of patients with diabetes, leading to vision loss in both working-age and elderly populations. Early detection and intervention can improve patient outcomes and reduce the burden on healthcare. By developing robust computational techniques, we can advance automated systems for screening and managing diabetic retinopathy. Our specific goal is to detect and segment exudates and hemorrhages in fundus images. In this study, we used the iterative NICK thresholding region growing (INRG) method as a basis. To further improve our results in different applications, we incorporated the watershed separation algorithm (WS) and the Chi