الخلاصة

The bifurcations and crossovers are important feature points, which play important roles in the analysis of the retinal vessel tree. More than 100 vascular bifurcations can be seen in a typical retinal fundus image. Their manual detection by a human observer is a tedious and time consuming process. This paper attempts to automate the detection of retinal vascular bifurcations and crossovers points and removing it from the image. We created a specific mask used to locate and recognize the nodes and crossover points in retinal fundus image. The results of implementing this proposed algorithm was reliable and very accurate.