Metal surface defect detection using iterative thresholding technique

Recently, surface defects detection in metals plays a significant role in computer vision applications. An efficient and accurate defect detection approach is implemented in this paper. The defect detection on metal surface is achieved by iterative thresholding technique on metal surface images. The defect region such as crack and shrinkage of the metal surface image is detected by binarization using iterative thresholding technique. The experimental results are carried out by using real time metal surface images and satisfactory performance is achieved by the proposed defect detection technique.