Complete edge information is essential to the detection of edge defects of turbine wind turbine blades. Due to the complex and diverse background of wind turbine blade ( WTB) images, the existing image segmentation algorithms have insufficient segmentation accuracy and cannot guarantee the integrity of edge defects. Therefore, an adaptive image segmentation based on image edge features and color information is proposed for the edge detection of WTBs. Firstly, Hough line detection is used to detect the blade edge at straight lines. Secondly, the Graph-cut algorithm based on Otus threshold segmentation and morphological operations is applied to adaptively separate the blade target areas. Finally, comparative experiments are carried out with a lot of image samples captured under various scenes. The results show that higher edge coverage and lower boundary displacement errors of the WTB image segmentation with 0. 971 7 and 3. 040 3 are obtained by the proposed method as compared with other image segmentation methods. The proposed approach has potential application value for the edge defect detection of WTBs.