边界聚类椭圆快速检测方法

doi:10.3785/j.issn.1008-973X.2016.03.002

浙江大学学报(工学版)

机械工程

边界聚类椭圆快速检测方法

吴尧锋1,3,王文2,卢科青2,魏燕定1,陈子辰1

1. 浙江大学机械工程学院浙江省先进制造技术重点实验室,浙江杭州 310027； 2. 杭州电子科技大学机械工程学院,浙江杭州310018； 3. 浙江大学宁波理工学院机电与能源工程学院,浙江宁波 315100

Fast ellipse detection based on edge grouping

WU Yao feng1,3, WANG Wen2, LU Ke qing2, WEI Yan ding1, CHEN Zi chen1

1.Key Lab of Advanced Manufacturing Technology of Zhejiang Province, School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China;2.School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China; 3.College of Mechanical and Energy Engineering, Institute of Technology, Zhejiang University, Ningbo 315100, China

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摘要：

针对多个椭圆因重叠、遮挡、嵌套情况而存在检测效率与精度较低的问题,提出一种基于边界聚类的椭圆快速检测改进方法.该方法包括图像预处理、边界聚类、椭圆拟合和去伪过程.进行图像预处理,包括边界检测、细化边界和消除冗余等价边界列(EELs),去除多数非椭圆边界像素.开展边界聚类,通过边界像素连接、线段列提取和圆弧聚类,得到一系列候选椭圆弧和椭圆弧对.采用直接最小二乘方法拟合椭圆,并作去伪处理.利用椭圆的形态信息,调整算法步骤、优化阈值,提高算法效率,并通过实验评估算法性能.结果表明,边界聚类方法可准确、快速检测不同形态的椭圆,改进后用时可缩短14%～76%.

Abstract:

An improved ellipse detection method based on edge grouping was proposed due to the low detection efficiency of multiple, overlapping, occluded and nested ellipses. The method consisted of image preprocessing, edge grouping, elliptical fitting and removal of false alarms. First, the majority of non elliptic boundary pixels were removed in the process of image preprocessing through edge detection, edge thinning and redundant EELs (equivalent edge lists) elimination. Then, a series of candidate elliptic arcs and elliptic arc pairs were obtained in the edge following process through edge linking, line segment list extraction, neighborhood and global merging of arcs. Ellipse fitting was performed by using direct least squares method, and the false alarms were subsequently removed. Besides, combined with the existing forms of target ellipses, the algorithm was simplified and the threshold was also optimized. Finally, the proposed method was evaluated by using both synthetic and real world images. Results show that the edge grouping method can detect ellipses accurately and fast in different existing forms, with 14%～76% time shortened after optimization．

出版日期: 2016-09-18

TP 391.73

基金资助:

国家自然科学基金资助项目（51275465）；浙江省自然科学基金重点资助项目（LZ16E050001）;浙江省科技计划公益资助项目（2014C31096）；浙江省先进制造技术重点实验室开放基金.

通讯作者: 王文，男，教授. ORCID：0000 0002 0084 0910. E-mail: wangwn@hdu.edu.cn

作者简介: 吴尧锋（1986-），男，博士生，从事逆向工程技术、数字化设计与制造研究.ORCID：0000 0002 6519 9693. E-mail：wuyaofeng@outlook.com

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引用本文:

吴尧锋,王文,卢科青,魏燕定,陈子辰. 边界聚类椭圆快速检测方法[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2016.03.002.

WU Yao feng, WANG Wen, LU Ke qing, WEI Yan ding, CHEN Zi chen. Fast ellipse detection based on edge grouping. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2016.03.002.

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http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2016.03.002 或 http://www.zjujournals.com/eng/CN/Y2016/V50/I3/405

［1］陈海峰, 雷华, 孔燕波, 等. 基于最小二乘法的改进的随机椭圆检测算法［J］. 浙江大学学报：工学版, 2008, 42(8): 1360-1364．
CHEN Hai feng, LEI Hua, KONG Yan bo, et al. An improved randomized algorithm for detecting ellipses based on least square approach ［J］. Journal of Zhejiang University: Engineering Science, 2008, 42(8): 1360-1364．
［2］ LIU H M, WANG Z H. Geometric property based ellipse detection method ［J］. Journal of Visual Communication and Image Representation, 2013, 24(7): 1075-1086．
［3］ ALVAREZ L, SALGADO A, SANCHEZ J. Robust detection and ordering of ellipses on a calibration pattern ［J］. Pattern Recognition and Image Analysis, 2007, 17(4): 508-522．
［4］ LEO M, MAZZEO P L, NITTI M, et al. Accurate ball detection in soccer images usin g probabilistic analysis of salient regions ［J］. Machine Vision and Applications, 2013, 24(8): 1561-1574．
［5］ USABIAGA J, EROL A, BEBIS G, et al. Global hand pose estimation by multiple camera ellipse tracking ［J］. Machine Vision and Applications, 2008, 21(1): 1-15．
［6］ HIROSE K, TORIU T, HAMA H. Estimation of vehicle wheelbase in a circular fisheye image using two step detection method of tire road contact points ［J］. International Journal of Innovative Computing,Information and Control, 2011, 7(8): 4717-4727．
［7］ CHEN K C, BOUGUILA N, ZIOU D. Quantization free parameter space reduction in ellipse detection ［J］. Expert Systems with Applications, 2011, 38(6): 7622-7632．
［8］ MEI B, ZHU W D, YAN G R, et al. A new elliptic contour extraction method for reference hole detection in robotic drilling ［J］. Pattern Analysis and Applications, 2014, 18(3): 695-712．
［9］ BAI X Z, SUN C M, ZHOU F G. Splitting touching cells based on concave points and ellipse fitting ［J］. Pattern Recognition, 2009, 42(11): 2434-2446．
［10］ NGUYEN T M, AHUJA S, WU Q M J. A real time ellipse detection based on edge grouping ［C］ ∥ International Conference on Systems,Man and Cybernetics, San Antonio: IEEE, 2009: 3280-3286．
［11］ MUKHOPADHYAY P, CHAUDHURI B B. A survey of Hough Transform ［J］. Pattern Recognition, 2015, 48(3): 993-1010．
［12］ MCLAUGHLIN R A. Randomized Hough transform: improved ellipse detection with comparison ［J］. Pattern Recognition Letters, 1998, 19(3/4): 299-305．
［13］屈稳太. 基于弦中点Hough变换的椭圆检测方法［J］. 浙江大学学报：工学版, 2005, 39(8): 1132-1135．
QU Wen tai. Chord midpoint Hough transform based ellipse detection method ［J］.Journal of Zhejiang University: Engineering Science, 2005, 39(8):1132-1135．
［14］ FITZGIBBON A, PILU M, FISHER R B. Direct least square fitting of ellipses ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1999, 21(5): 476-480．
［15］ RAY A, SRIVASTAVA D C. Non linear least squares ellipse fitting usin g the genetic alg orithm with applications to strain analysis ［J］. Journal of Structural Geology, 2008, 30(12): 1593-1602．
［16］ PRASAD D K, LEUNG M K H, CHOS S. Edge curvature and convexity based ellipse detection method［J］. Pattern Recognition. 2012, 45(9): 3204-3221．
［17］ CHATBRI H, KAMEYAMA K. Using scale space filtering to make thinning algorithms robust against noise in sketch images ［J］. Pattern Recognition Letters, 2014, 42: 1-10．
［18］ ONIGA F, MIRON M, DANESCU R, et al. Automatic recognition of low earth orbit objects from image sequences ［C］ ∥ 7th International Conference on Intelligent Computer Communication and Processing. Cluj Napoca: IEEE, 2011: 335-338．
［19］ MATLAB and Octave Functions. ［EB/OL］. (2013 08 02)［2015 02 07］. http:∥www.csse.uwa.edu.au/～pk/research/matlabfns/．
［20］ GUO Y, SOHEL F, BENNAMOUN M, et al. A novel local surface feature for 3D object recognition under clutter and occlusion ［J］. Information Sciences, 2015, 293: 196-213．

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