In　this　paper,　we　present　an　algorithm　for　the　effective　segmentation　of　retinal　blood　vessels　in　vessel　quantization　for　assessing　the　risk　of　cerebrovascular　diseases.　Given　that　the　vessel　is　the　highlight　of　the　fundus　image　and　has　a　characteristic　texture,　we　adopt　color　and　texture　as　the　saliency　features　for　vessel　extraction　combined　with　region　optimization.　The　optimal　thresholding　can　be　obtained　through　the　gray　histogram　thresholding　method　to　segment　the　vessel.　Moreover,　morphological　operators　are　applied　to　preserve　the　remaining　small　vessels　considering　the　loss　of　small　vessels.　Experiments　are　designed　to　evaluate　the　performance　of　the　proposed　models　with　more　than　94%　accuracy.　Experimental　results　reveal　that　the　blood　vessel　can　be　effectively　detected　by　applying　our　method　on　the　retinal　images.　©　2017,　©　The　Author(s)　2017.