Coherent chord computation and cross ratio for accurate ellipse detection

doi:10.1016/j.patcog.2023.109983

	Coherent chord computation and cross ratio for accurate ellipse detection
	Zhao, Mingyang 1,2,3; Jia, Xiaohong 4; Ma, Lei1,5 ; Hu, Li-Ming 6; Yan, Dong-Ming2,3,6
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
	2024-02-01
卷号	146 页码:16
通讯作者	Jia, Xiaohong(xhjia@amss.ac.cn) ; Ma, Lei(lei.ma@pku.edu.cn)
摘要	This paper presents a new method for detecting ellipses in images, which has many applications in pattern recognition and robotic tasks. Previous approaches typically use sophisticated arc grouping strategies or calculate differential such as tangents, and thereby they are less efficient or more sensitive to noise. In this work, we present a novel ellipse detector, based on the simple yet effective chord computation, and on the projective invariant cross ratio, which achieves promising performance in both accuracy and efficiency. First, elliptical arcs are extracted by fast vector computations along with the removal of straight segments to speed up detection. Then, arcs from the same ellipse are grouped together according to the relative location and the intersecting chord constraints, both are on coherent chord computation without differential. Additionally, an efficient additive principle is applied to further accelerate the grouping process. Finally, a novel and robust verification by area-deduced cross ratio is introduced to pick out salient ellipses. Compared with predecessor methods, cross ratio is not only simple for computation, but also has invariant properties (used to discriminate ellipses). Extensive experiments on seven public datasets (including synthetic and real-world images) are implemented. The results highlight the salient advantages of the proposed method compared to state-of-theart detectors: Easier to implementation, more robust against occlusion and noise, as well as attaining higher F-measure.
关键词	Ellipse detection Chord computation Cross ratio Hough transform
DOI	10.1016/j.patcog.2023.109983
收录类别	SCI
语种	英语
资助项目	Na-tional Key Research and Development Program of China[2020YFB1708900] ; National Natural Science Foundation of China[12022117] ; National Natural Science Foundation of China[62172415] ; CAS Project for Young Scientists in Basic Research[YSBR-034] ; Open Research Fund Program of State key Laboratory of Hydroscience and Engineering, Tsinghua University[sklhse-2022-D-04]
项目资助者	Na-tional Key Research and Development Program of China ; National Natural Science Foundation of China ; CAS Project for Young Scientists in Basic Research ; Open Research Fund Program of State key Laboratory of Hydroscience and Engineering, Tsinghua University
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:001088526900001
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/54305
专题	多模态人工智能系统全国重点实验室多模态人工智能系统全国重点实验室_三维可视计算
通讯作者	Jia, Xiaohong; Ma, Lei
作者单位	1.Beijing Acad Artificial Intelligence, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, MAIS, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, NCMIS, KLMM, Beijing, Peoples R China 5.Peking Univ, Coll Future Technol, Natl Biomed Imaging Ctr, Beijing, Peoples R China 6.Tsinghua Univ, State Key Lab Hydrosci & Engn, Beijing, Peoples R China
第一作者单位	中国科学院自动化研究所; 模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhao, Mingyang,Jia, Xiaohong,Ma, Lei,et al. Coherent chord computation and cross ratio for accurate ellipse detection[J]. PATTERN RECOGNITION,2024,146:16.
APA	Zhao, Mingyang,Jia, Xiaohong,Ma, Lei,Hu, Li-Ming,&Yan, Dong-Ming.(2024).Coherent chord computation and cross ratio for accurate ellipse detection.PATTERN RECOGNITION,146,16.
MLA	Zhao, Mingyang,et al."Coherent chord computation and cross ratio for accurate ellipse detection".PATTERN RECOGNITION 146(2024):16.