Diabetic Retinopathy is a medicinal condition in which the retina is impaired based on fluid breaks from veins into the retina. The occurrence of hemorrhages in the retina is the most prompt effect of diabetic retinopathy. The number and state of hemorrhages are used to display the significance of the disorder. This research paper analyzed hemorrhage detection in retinal fundus images using classifier and segmentation methods. All the database images into the pre-processing steps and some meaning full features are extracted from the images. Then ANFIS classifier utilized to normaland abnormal images, this abnormal category into the hemorrhage detection process with help of segmentation technique. Here Region growing (RG) with threshold optimization techniques are considered its known as Modified RG (MRG) to get the maximum accuracy in the hemorrhage segmenting process. As regards the threshold optimization, Grey Wolf Optimization (GWO) technique used, this proposed work compared to our existing work getting maximum accuracy, sensitivity and specificity performance metrics.