An anisotropic diffusion-based defect detection for sputtered surfaces with inhomogeneous textures

Texture analysis techniques are being increasingly used for surface inspection, in which small defects that appear as local anomalies in textured surfaces must be detected. Traditional surface inspection methods mainly focus on homogeneous textures that contain periodical, repetitive patterns. In this paper, we study defect detection in sputtered glass substrates that involve inhomogeneous textures. Such sputtered surfaces can be found in touch panels and LCDs. An anisotropic diffusion scheme is proposed to detect subtle defects embedded in inhomogeneous textures. The proposed anisotropic diffusion model takes a nonnegative decreasing function with an annealing gradient threshold as the diffusion coefficient to adaptively adjust the significance of edge gradients. It triggers the smoothing process in faultless areas for background texture removal by assigning a large diffusion coefficient value, and stops the diffusion process in defective areas to preserve sharp edges of anomalies by assigning a small diffusion coefficient value. Experimental results from a number of sputtered glass samples have shown the effectiveness of the proposed anisotropic diffusion scheme.