ABSTRACT:In the construction field, the bolting robot provides convenience and reduces a process time of assembling steel frames. When assembling steel frames, the bolting robot finds a bolt hole with the help of camera. If the light conditions are either too bright or too dark, however, it is hard to find a bolt hole in the input image because the contrast between bolt hole and background is vague. In order to improve detection accuracy in such environment, this paper proposes the image processing algorithm using template matching (TM). First, the input image is converted from RGB to YCbCr in order to reduce influence of shadow. Then we separate Y channel of image in darkness or extract edges from Cb and Cr channel of image in brightness. Template image is created with the radius which can be calculated with the distance to a steel frame. We used TM to create the normalized cross correlation (NCC) image which shows correlation between processed image and template. Finally, bolt holes are extracted from the high-correlation part of NCC image. Experimental results show that the proposed method is robust to detect bolt holes under various illumination conditions.
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.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.