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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.