A roll of steel might have various defects of scratch, stains, and chisel mark after slitting process. However, the traditional steel surface inspection method is via the human inspection that not only takes amount of time but also causes inconsistent inspection consequences. As a result, this paper proposed an in-line visual inspection hardware and software system. The hardware is composed of upper and lower optical module. The defect inspection algorithm includes automatic region of interesting (ROI) searching and defect detection by using Sobel method. Experimentations revealed that the successful detection rate is up to 80% and the inspection speed of per image with 3K in width and 1K in length is less than 80 milliseconds. The contribution is that the proposed method can provide suitable inspection results of the steel surface defect and meet the steel industry demands.
3-D profilometry, it is necessary to locate the in-focus region of the image and to reconstruct the best 3D
profile. A series of images are collected on-the-fly. The contrast and the intensity indices of each region of
each image are calculated in the scanning procedure. The proposed method will reconstruct 3D shape from
moving platform. The proposed method is applied on some preliminary experiments and it shows that the
large-scale 3-D profile reconstruction can be realized.