Efficient detection of retina blood vessels using Proficient morphological algorithms

Image processing play a vital role in blood vessel extraction from the fundus image. Retinal vessel segmentation is important for the detection of eye diseases and plays an important role in automatic retinal disease screening systems. Automatic detection and analysis of the vasculature can assist in the implementation of screening programs for vessel diameter measurement in relation with diagnosis of hypertension, and computer-assisted laser surgery. Segmentation retinal anatomical structures are the first step in any automatic retina analysis system. Detection of large vessels is relatively easy due to their strong contrast against background in the images but detection of small vessels is much more difficult due to their low contrast in the images. The proposed method uses a new filter to extract the thin vessels. Also the proposed method has been tested with various set of retinal images. The images used for retinal analysis were collected from DRIVE database.