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A hybrid method for ellipse detection in industrial images
Chen SL(陈松林); Xia RB(夏仁波); Zhao JB(赵吉宾); Chen YL(陈月玲); Hu MB(胡茂邦)
Department装备制造技术研究室
Source PublicationPattern Recognition
ISSN0031-3203
2017
Volume68Pages:82-98
Indexed BySCI ; EI
EI Accession number20171603586478
WOS IDWOS:000401381100007
Contribution Rank1
Funding OrganizationNatural Science Foundation of China [51375476]
KeywordEllipse Detection Edge Following Method Hough Transform Industrial Application Reliability
AbstractMany ellipse detection methods have been proposed for detecting ellipses in images. However, they are unsuitable for industrial images due to low signal-to-noise ratios (SNR). This paper presents an ellipse detection method combining the advantages of Hough transform(HT) based methods and the advantages of edge following methods, which is capable of detecting fragmented ellipses and is both computational and memory efficient. Our method works in two steps. In the first step, an edge following method is proposed to quickly and accurately extract the majority of ellipses. For ellipses missed in the first step, candidate regions where each may contain one missed ellipse are extracted in the second step using cluster analysis, and then a HT based method is performed on these regions to extract the missed ellipses. This can not only guarantee the accuracy of the HT based method, but also save the memory and computation time. We test the performance of our method using both synthetic images and low SNR industrial images. Experimental results demonstrate that the proposed method performs far better than existing methods in terms of recall, precision, F-measure, and reliability. Especially in term of reliability, our method has achieved a very high value close to 1 while the reliabilities of state-of-the art methods are almost less than 0.5.
Language英语
WOS HeadingsScience & Technology ; Technology
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS KeywordRANDOMIZED HOUGH TRANSFORM ; ROBUST ; NOISE
WOS Research AreaComputer Science ; Engineering
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/20366
Collection智能产线与系统研究室
Corresponding AuthorXia RB(夏仁波)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, No. 114, Nanta Road, Shenyang, Liaoning 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
Recommended Citation
GB/T 7714
Chen SL,Xia RB,Zhao JB,et al. A hybrid method for ellipse detection in industrial images[J]. Pattern Recognition,2017,68:82-98.
APA Chen SL,Xia RB,Zhao JB,Chen YL,&Hu MB.(2017).A hybrid method for ellipse detection in industrial images.Pattern Recognition,68,82-98.
MLA Chen SL,et al."A hybrid method for ellipse detection in industrial images".Pattern Recognition 68(2017):82-98.
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