Diabetic retinopathy is the cause for blindness in the human society. Early detection of it prevents blindness. Image processing techniques can reduce the work of ophthalmologists and the tools used to detect Diabetic Retinopathy Patients. Proliferative diabetic retinopathy is the most advanced stage of diabetic retinopathy, and is classified by the growth of new blood vessels. These blood vessels are abnormal and fragile, and are susceptible to leaking blood and fluid onto the retina, which can cause severe vision loss. First, vessel like patterns are segmented by using Ridge Strength Measurement and Watershed lines. The second step is measuring the vessel pattern obtained . Many features that are extracted from the blood vessels such as shape, position, orientation, brightness, contrast and line density have been used to quantitative patterns in retinal vasculature. Based on the seven features extracted, the segment is classified as normal or abnormal by using Support Vector Machine Classifier . The obtained accuracy may be sufficient to reduce the workload of an ophthalmologist and to prioritize the patient grading queues.