Segmentation of Blood Vessels in Retinal Images based on Nonlinear Filtering

This paper describes a methodology for the segmentation of blood vessels in digital images of human eye retina. The proposed method is based on the background subtraction between a filtered retinal image by anisotropic diffusion and an approximation of the retinal background, obtained by a median filtering. The subtraction operation results in an image of differences, which is enhanced by a local histogram stretching and thresholded to detect the blood vessels. Finally, the obtained binary image is filtered aiming to remove small signals and false responses which are related to retina pathologies. We evaluated the proposed method using STARE and DRIVE image sets, in which the results have shown higher accuracy rates when compared with similar approaches.