Open AccessAngle aided circle detection based on randomized Hough transform and its application in welding spots detection
Author(s) -
Liang Qiao,
Jianyong Long,
Yang Nan,
Gianmarc Coppola,
Kun Zou,
Dan Zhang,
Wei Sun
Publication year - 2019
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2019060
Subject(s) - hough transform , artificial intelligence , computer vision , computation , computer science , algorithm , image processing , image (mathematics) , sampling (signal processing) , mathematics , filter (signal processing)
The Hough transform has been widely used in image analysis and digital image processing due to its capability of transforming image space detection to parameter space accumulation. In this paper, we propose a novel Angle-Aided Circle Detection (AACD) algorithm based on the randomized Hough transform to reduce the computational complexity of the traditional Randomized Hough transform. The algorithm ameliorates the sampling method of random sampling points to reduce the invalid accumulation by using region proposals method, and thus significantly reduces the amount of computation. Compared with the traditional Hough transform, the proposed algorithm is robust and suitable for multiple circles detection under complex conditions with strong anti-interference capacity. Moreover, the algorithm has been successfully applied to the welding spot detection on automobile body, and the experimental results verifies the validity and accuracy of the algorithm.