Textural defect segmentation using a Fourier-Domain maximum likelihood estimation method

When automatically inspecting textured surface defects, the most important step is to segment the defects from the background. For complicated textures, however, defect segmentation is still a challenging problem. In this paper, we use a Fourier-domain maximum likelihood estimator (FDMLE) based on the fractional Brownian motion (FBm) model to inspect surface defects of textile fabrics. From the experiments, we obtain good results for defect segmentation, and find the method's performance is invariant under geometric transformation.