Comparative Analysis of Edge Detection Techniques for Extracting Blood Vessels in Diabetic Retinopathy

Abstract

Diabetic retinopathy (DR) is one of the serious complications caused by diabetes. It damages the small blood vessel of the retina, which leads to loss of vision. Accurate extraction of retinal blood vessels is an important task in computer-aided diagnosis of DR. The edge detection technique has been greatly benefited in interpreting the information contents in the retinal blood vessel. The preprocessing of retinal image may help in detecting the early stage of symptoms in DR. In this article, we compared the results of Sobel and Canny edge operators for finding the abnormalities in retinal blood vessels. The Canny operator is found to be more accurate in detecting even tiny blood vessels compared to Sobel operator for an affected diabetic retinal image. The peak signal-to-noise ratio (PSNR) is also found to be high in the Canny operator.