Abstract
Conventional Hough based circle detection methods are robust, but for computers in last century, it is to slow and memory demanding. With the rapid development of computer hardware, Hough transform is acceptable now. Improvement on Hough based circle detection is valuable. In this paper, we present a novel curvature aided Hough transform for circle detection (CACD) algorithm, which estimates the circle radius from curvature. Curvature pre-estimation is capable to avoid both accumulating operations of all the points and interruption between different scales, which result in faster and more precise circle detection. Compared to the conventional Hough-based algorithm for circle detection, the algorithm is more practical and less time consuming. Its time taking is about 1/8 of that of conventional algorithm. Test results on traffic sign images shown that The CACD gets an AUC (Area Under Curve) of 0.9125. The CACD is capable to detect circles of different radius in complex scene.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.