Abstract— Blood vessel segmentation from the retinal image is useful in detecting ocular disorders and laser surgery, the work done till the date for segmentation of blood vessels are satisfactory in some cases, still leave room for improvement, especially in abnormal retinal images. Clustering and pattern analysis are the new technique which are widely used now a days for medical image processing. This paper proposes a method of blood vessel segmentation from the retinal images using a soft clustering method known as Fuzzy C Means clustering (FCM) which assigns membership values to the pixels instead of separating the pixels as in hard clustering problems and the clustering is optimized using recently developed swarm based algorithm Artificial Bee Colony (ABC) optimization.

Index Terms— Fundus camera, Clustering, Fuzzy C means, Artificial bee colony optimization

Cite: Maaneesh P and Chaya H P, "RETINAL BLOOD VESSEL SEGMENTATION BY FCM CLUSTERING AND ARTIFICIAL BEE COLONY OPTIMIZATION," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 4, No. 3, pp. 21-26, July 2015.