In this study, we propose retinal vessel segmentation based on fuzzy C-means (FCM) clustering in accordance with the local line structural constraints. The pixel features are extracted via multi-scale match filter and B-COSFIRE filter of the pre-processed image, where the contrast between the vessel and the background is enhanced. Thus, retinal vessel segmentation can be realized using the FCM clustering algorithm according to the local line structural constraints. Finally, the isolated noise points are eliminated via the post-processing operation. The experiment is performed using the DRIVE database. The average accuracy, sensitivity, and specificity are 94.21%, 67.21%, and 98.2%, respectively. When compared with the traditional feature-space-based FCM algorithm, the proposed method exhibits better continuity with respect to the segmented retinal vessels and is more sensitive to the small blood vessels.