This invention relates to the field of
computer vision technology, and in particular to a method for identifying surface defects in wind
turbine metal parts based on
image processing. The method acquires
grayscale images of the wind
turbine metal parts at each
exposure time, designating any
grayscale image as the target image. For any pixel in the target image, an initial fusion weight is obtained based on the difference between the local
grayscale distribution of that pixel and the grayscale distribution of pixels in the target image. The initial fusion weight is then adjusted based on the local detail features and the degree of local
noise interference of that pixel to obtain the final fusion weight. The final fusion weight and
irradiance of each pixel in each grayscale image are obtained, and the fused
irradiance corresponding to each pixel in the target image is obtained. Finally, the final image of the wind
turbine metal parts is obtained using the fused
irradiance of each pixel in the target image, improving the accuracy of defect identification using the final image.