Segmentation of retinal blood vessels is a very important diagnostic procedure in ophthalmology. Segmenting blood vessels in the presence of pathological lesions is a majorchallenge. In this paper, an innovative approach to segment the retinal blood vessel in thepresence of pathology is proposed. The method combines both supervised and unsupervised approaches in the retinal imaging context. Two innovative descriptors named localHaar pattern and modified speeded up robust features are also proposed. Experiments areconducted on three publicly available datasets named: DRIVE, STARE and CHASE DB1,and the proposed method has been compared against the state-of-the-art methods. Theproposed method is found about 1% more accurate than the best performing supervisedmethod and 2% more accurate than the state-of-the-art Nguyen et al.’s method.