An automated vessel segmentation algorithm in retinal images using 2D Gabor wavelet

This paper proposes a novel method to extract blood vessels in retinal images. We also present a new effective preprocessing to reduce the effect of non-uniformly illumination using red and green channels of these images. The vessels finally have been extracted using 2D Gabor filter bank followed by thresholding on grayscale and thresholding based on structural properties of labeled vessel candidates, to extract large and thin vessels. The proposed algorithm is evaluated on DRIVE database, which is publically available. The results show that presented algorithm achieved accuracy rate of 94.81% along with True Positive Fraction (TPF) of 71.12% and False Positive Fraction (FPF) of 2.84%.