Blood Vessels Extraction using Green Channel Extraction

Diabetic retinopathy is a vision-threatening illness caused by diabetes. It has the potential to cause blindness in people of working age. By detecting and analyzing, the architecture of the vasculature in retinal pictures can be seen. By detecting diabetes in its early stages, you can prevent it from progressing. The condition of retinal blood vessels is compared. Blood vessel segmentation is presented in this study. Method that can be employed in computer assisted retinal imaging the retinal image vessels were extracted using image analysis. By using K-means clustering and mathematical morphology the vessels were segmented. Mathematical morphology is used to smooth the retinal image in order to emphasize on the blood vessels and to reduce the background information. Then there’s the improved K-means clustering is used to segment the image algorithm. The proposed strategy proved to be beneficial as the average accuracy is 95.10% and the best accuracy is 96.25%.