Abstract: The method for crack damage identification,crack type judgment and feature parameter extraction of wind turbine blades based on digital image processing technology is studied in order to realize the high efficiency,intelligence and convenience of wind turbine blade damage detection. Different algorithms of the graying,filtering and threshold segmentation image processing steps are compared using blade images collected by the drone. The morphological processing method is improved. Firstly,the average value method is selected to conduct grayscale processing on the blade image. Secondly,the median filter is used to denoise the image.Thirdly,the Otsu threshold segmentation method is used to achieve the segmentation of the crack area. Then the perfect blade crack damage area is extracted based on the optimized morphological method,and finally the crack area is framed based on the connected domain principle. A wind turbine blade crack damage identification system is designed based on the above selected and improved algorithms to realize the visual processing of blade crack image detection,crack type judgment and crack feature parameter extraction.The results show that the system has reliable identification accuracy for the crack damage detection of wind turbine blades,and the identification accuracy is 85%. The designed system realizes the automatic identification and feature parameter extraction of wind turbine blade crack damage,and improves the detection efficiency of blade crack damage.