Detection of Blood Vessels in Retinal Images using Line Tracking Algorithm

Several pathological diseases in the eye could be easily identified through the retinal blood vessels. Thus, the blood vessels of the retina play an important role in the medical field segmentation and analysis. Although many supervised and unsupervised algorithms and methods exist for the extraction and processing of retinal blood vessels, they do not produce the best outputs with retinal images that are poor in contrast and details. Certain algorithm like Kirsch edge detection method, do produce good results for low contrast images but fail to provide results for the thin blood vessels present in the retina. In this paper, we propose a line tracking algorithm that provides accurate segmentation results even for the thinnest blood vessel present by using threshold concept. It also outputs the best results of map quantization without masking.