A thresholding based technique to extract retinal blood vessels from fundus images

Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract retinal blood vessels, (iii) post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases respectively.