Aiming at the issues that the real time is not strong and the segmenta tion accuracy is not high in majority of retinal blood vessel extraction algorithms,a fast retinal blood ve ssel extraction algorithm based on controlled image segmentation is proposed.Firstly,the intensity of the green c hannel image is inversed and adaptive histogram equalization is applied,the morphological ‘opening’ opera tion is conducted using the ‘diamond’ structuring element and the ‘disc’ structuring element to smooth t he image background and highlight the blood vessels,the optical disk is removed before binarizing the image by thres holding method,and the segmented image without the optical disk is obtained.Sec ondly,a mask is created based on the optic disc detected in grayscale image,the green component image is also applied with ada ptive histogram equalization and threshold segmentation,after which the segmented image with a mask is obta ined using ‘AND’ logic operation with the mask.Finally,the segmented image with noise removed is compared with that wi th a mask according to ‘AND’ logic operation,and the final image of blood vessels is obt ained together with the border information.The experiment results indicate that the proposed algorithm can effectively detect t he blood vessels’ network of fundus image,and it also has strong real time ability and high segmentation accuracy.