Defect inspection system for steel wire rods produced by hot rolling process

A vision-based inspection system has been investigated in order to improve the quality of products and processes found in various industries. In this paper, we propose a new defect detection algorithm for steel wire rods produced by the hot rolling process. Because the steel wire rods are long cylinder rods with a circular cross section, the brightness at the sides and center is inconsistent. Moreover, the various types of steel wire rods and the presence of scales affect the reflection properties of the rod surface. In order to resolve the abovementioned difficulties, the use of dynamic programming and a discrete wavelet transform are proposed. An adaptive local binarization method is used to further reduce the effects of scale. The effectiveness of the proposed method is shown by means of experiments conducted on images of steel wire rods that were obtained from an actual steel production line.