Vessel centerline detection in retinal images based on a corner detector and dynamic thresholding

Abstract

This paper describes a new method for the calculation of the retinal vessel centerlines using a scale-space approach for an increased reliability and effectiveness. The algorithm begins with a new vessel detector description method based on a modified corner detector. Then the vessel detector image is filtered with a set of binary rotating filters, resulting in enhanced vessels structures. The main vessels can be selected with a dynamic thresholding approach. In order to deal with vessels bifurcations and vessels crossovers that might not be detected, the initial retinal image is processed with a set of four directional differential operators. The resulting directional images are then combined with the detected vessels, creating the final vessels centerlines image. The performance of the algorithm is evaluated using two different datasets.