An occlusion-resistant circle detector using inscribed triangles
Zhao, Mingyang1,3; Jia, Xiaohong1,3; Yan, Dong-Ming2,3
AbstractCircle detection is a critical issue in pattern recognition and image analysis. Conventional geometry-based methods such as tangent or symmetry are sensitive to noise or occlusion. Area computation is more robust against noise, because it avoids differential calculations. Inspired by this characteristic, we present a novel method for fast circle detection using inscribed triangles. The proposed algorithm, which is robust to noise and resistant to occlusion, first extracts circular arcs by approximating line segments and identifying inflection points and sharp corners. To speed up the computation, irrelevant segments are filtered out through the triangle inequality. Arcs that belong to the same circle are then combined according to the position constraint and the inscribed triangle constraint. The circle parameters are further estimated by inscribed triangles based upon the Theil-Sen estimator and linear error refinement without the dependence of least-square fitting but still with the equivalent accuracy. Finally, candidate circles are verified to prune false positives through an inlier ratio rule, which jointly considers both distance and angle deviations. Extensive experiments are conducted on synthetic images including overlapping circles, and real images from four diverse datasets (three publicly available and one we built). Results are compared with those of representative state-of-the-art methods, and the proposed method is demonstrated to embraces several advantages: resistant to occlusion, more robust to noise, and better performance and efficiency. (C) 2020 Elsevier Ltd. All rights reserved.
KeywordCircle detection Inscribed triangle Parameter estimation Hough transform
Indexed BySCI
Funding ProjectNational Natural Science Foundation of China[61872354] ; National Natural Science Foundation of China[61772523] ; National Key R&D Program of China[2019YFB2204104] ; Beijing Natural Science Foundation[L182059] ; Beijing Natural Science Foundation[Z190004] ; Intelligent Science and Technology Advanced subject project of University of Chinese Academy of Sciences[115200S001] ; Open Research Fund Program of State key Laboratory of Hydroscience and Engineering, Tsinghua University[sklhse-2020-D-07] ; Alibaba Group through Alibaba Innovative Research Program
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000573025400001
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Document Type期刊论文
Corresponding AuthorJia, Xiaohong
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, NCMIS, KLMM, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Mingyang,Jia, Xiaohong,Yan, Dong-Ming. An occlusion-resistant circle detector using inscribed triangles[J]. PATTERN RECOGNITION,2021,109:15.
APA Zhao, Mingyang,Jia, Xiaohong,&Yan, Dong-Ming.(2021).An occlusion-resistant circle detector using inscribed triangles.PATTERN RECOGNITION,109,15.
MLA Zhao, Mingyang,et al."An occlusion-resistant circle detector using inscribed triangles".PATTERN RECOGNITION 109(2021):15.
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