Retinal blood vessel segmentation using gabor filter and top-hat transform

Retinal blood vessel segmentation is a widely used process in diagnosis of various diseases such as diabetic retinopathy, glaucoma and arteriosclerosis. Therefore, an automated tool developed for vessel segmentation could be employed in diagnosis of those illnesses to help ophthalmologists. In this paper, we suggest a method to segment retinal blood vessels automatically. In the method, we apply top-hat transform after Gabor filter to enhance blood vessels. Later on, the output of the transformation is converted to binary image with p-tile thresholding. In order to test the developed system 20 images obtained from STARE database are used for performance evaluation. The results shows 86.31% of true positive rate (sensivity) and 92.90% of accuracy, which is promising.