S. Sukanya, S. Abinaya and D. Tamilselvi, Thiagarajar College of Engineering, India

The proposed method measures the retinal blood vessel diameter to identify arteriolar narrowing, arteriovenous (AV) nicking, branching coefficients to detect early diabetic retinopathy. It utilizes the vessel centerline and edge information to measure the width for a vessel segment. From the input retinal image, the vascular network is extracted using the local entropy thresholding method. The vessel boundaries are extracted using sobel edge detection method. The skeletonization operation is applied to the vascular network and mapping the vessel boundaries and the skeleton image. The branching point detection method is then performed to localize all crossing locations. A rotational invariant mask to search the pixel pairs from the edge image, and calculate the shortest distance pair which provides the vessel width (or diameter) for that cross-section. Variation in the width measurement identifies the diabetic retinopathy.

Computer Vision, Image Processing, Edge Detection, Mapping, Diabetic Retinopathy.