Steel-surface defect detection using a switching-lighting scheme

In this paper a novel filtering scheme combined with a lighting method is proposed for defect detection in steel surfaces. A steel surface has non-uniform brightness and various shaped defects, which cause difficulties in defect detection. To solve this problem we propose a sub-optimal filtering that is combined with a switching-lighting method. First, dual-light switching lighting (DLSL) is explained, which decreases the effect of non-uniformity of surface brightness and improves the detection accuracy. By using the DLSL method, defects are represented as alternated black and white patterns regardless of the size, shape, or orientation of defects. Therefore, defects can be detected by finding alternated black and white patterns. Second, we propose a scheme for detecting defects in steel-surface images acquired using the DLSL method. The presence of scales strongly affects the optical properties of the surface. Moreover, the textures of steel-plate images vary greatly because of the temperature and grade of steel. Therefore, conventional filter-design methods are not effective for different image textures. A sub-optimal scheme based on an optimized general-finite impulse-response filter is also proposed. Finally, experimental results conducted on steel-surface images from an actual steel-production line show the effectiveness of the proposed algorithm.