A Study on Digital Fundus Images of Retina for Analysis of Diabetic Retinopathy

Diabetes is a disorder that occurs due to high level of blood sugar in the body. Diabetes creates eye deficiency called as diabetic retinopathy. The symptoms in the retina area are fluid drip, exudates, hemorrhages, and microaneurysms. In modern medical science, images are important tool for precise diagnosis. This paper presents a study on retina images for analysis of diabetic retinopathy. The edges contain great deal of information about the locations of the objects, their shapes, and their sizes. Edge detection is basically a method of segmenting an image into regions of discontinuity. It plays an important role in digital image processing and a practical aspect of life. The analysis begins with preprocessing by converting RGB image into grayscale image. Then, the grayscale image has been converted into a binary image and lastly removing noise by using median filter. After that, various edge detectors like Canny edge detector, Laplacian of Gaussian, Prewitt and Sobel operators are used for edge detection of a digital fundus image. The statistical measurement in terms of accuracy 95%, sensitivity 94%, and specificity of 96% was obtained for edge detection by Sobel operator. This method outperforms compared to other edge detection techniques.