Retinal Blood Vessel Segmentation Using Gabor Filter and Morphological Reconstruction

Extraction of blood vessels in retinal images is helpful for ophthalmologists to screen a large number of medical disorders. The changes in the retinal vessels due to pathologies can be easily identified by the retinal vessel segmentation. Therefore, in this paper, we propose an automatic method to extract the blood vessels from various normal and abnormal retinal images. Our proposed method uses the advantages of the optimal Gabor filter and morphological reconstruction to employ robust performance analysis to evaluate the accuracy and sensitivity. Moreover, unsharp filter is used which sharpens the edges of the vessels without increasing noise. Our proposed algorithm proves its better performance by achieving the greatest accuracy, sensitivity, and specificity for the DRIVE and the STARE databases respectively. The results illustrate the superior performance of the proposed algorithm when they compared to other existing vessel segmentation methods.