Automated Retinal Blood Vessel Segmentation Using Fuzzy Mathematical Morphology and Morphological Reconstruction

Assessment of blood vessels in retinal images is an important factor for the many medical disorders. The retinal vessel evaluation can be done by first extracting the retinal images from the background. The changes in the retinal vessels due to the pathologies can be easily identified by segmenting the retinal vessels. In this paper we describe an automatic method for retinal blood vessels segmentation. Segmentation of retinal vessels is done to identify the early diagnosis of the disease like glaucoma, diabetic retinopathy, macular degeneration, hypertensive retinopathy and arteriosclerosis. In this the blood vessel is segmented using fuzzy morphological operation with the disc shaped structuring element and morphological reconstruction. This method is applied on the publicly available DRIVE database and the experimental results obtained by using green-channel images have been presented. This algorithm has been shown to be a very effective method to detect retinal blood vessels. Our proposed algorithm is simple, easy to be implemented, and the best suited for fast processing applications.