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Issue title: Artificial Intelligence and Advanced Manufacturing (AIAM 2020)
Guest editors: Shengzong Zhou
Article type: Research Article
Authors: Zhou, Lanfeng; * | Li, Ling
Affiliations: Shanghai Institute of Technology, Shanghai, China
Correspondence: [*] Corresponding author. Lanfeng Zhou, Shanghai Institute of Technology, Shanghai, China. E-mail: lfzhou@sit.edu.cn.
Abstract: Traditional Hough circle detection algorithm usually determines the center and radius of a circle by mapping points in cartesian coordinate system to polar coordinate system. Since it accumulates in the three-dimensional space, it requires more calculation consumption. In this paper, we solve the problem of high time complexity of Hough algorithm in judging circle radius and circle center from two aspects of circle angle and circle radius according to the geometric features of quasi-circles. A large number of experiments show that, compared with the traditional algorithm, this algorithm can not only identify quasi-circles, but also improve the detection success rate of circles by about 10%, with efficient running speed, and obtain good experimental results in the detection of craters.
Keywords: Hough transform, crater recognition, pattern recognition, edge detection, geometric features
DOI: 10.3233/JIFS-189707
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4469-4477, 2021
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