In order to discover distinct infection circumstances within blood veins, medical professionals frequently examine
tissue layer blood vessels using retinal images. The automatic recognition of retinal veins would make it easier to diagnose
numerous diseases. As a result, the time required for comprehensive eye examinations by the optometric MD is reduced. This
study's main purpose is to create attached tips for tracing blood veins in the tissue layer. To extract the retinal vas network from
anatomical structure images, the proposed methodology was devised. Our method is divided into four stages: first, preprocessing
in case you want to organize your dataset for segmentation; second, an image enhancement method that includes CLAHE with
Sequential filter; third, a Robinson compass mask for feature extraction; and fourth, a K-means clustering approach
agglomeration for higher segmentation. Lastly, a new process step that eliminates incorrectly divided remote regions was added.
