Angle aided circle detection based on randomized Hough transform and its application in welding spots detection.

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2019
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Abstract
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.
Reference Key
liang2019anglemathematical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Liang, Qiao Kang;Long, Jian Yong;Nan, Yang;Coppola, Gianmarc;Zou, Kun Lin;Zhang, Dan;Sun, Wei;
Journal mathematical biosciences and engineering : mbe
Year 2019
DOI
10.3934/mbe.2019060
URL
Keywords
angle aided randomized hough transform circle detection image processing machine vision welding spot

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