ELLIPSE FITTING BY ACCUMULATING 5-POINT FITS

被引：52
|
作者：
ROSIN, PL
机构：
[1] Cognitive Systems Group, School of Computing Science, Curtin University of Technology, Perth
来源：
PATTERN RECOGNITION LETTERS | 1993年 / 14卷 / 08期
关键词：
ELLIPSE FITTING; MEDIAN; LEAST SQUARES; HOUGH TRANSFORM;
D O I：
10.1016/0167-8655(93)90052-F
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Standard techniques for ellipse fitting such as the least squares method and the Hough Transform either make certain assumptions about the type of noise distribution, or require input parameters. This often prevents the techniques working robustly over a large range of data. A technique for ellipse fitting is described in this paper that does not have these disadvantages. It is based on accumulating many five-point ellipse fits to subsets of the data, sorting the parameters of these ellipses, and selecting the medians of each parameter.
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页码：661 / 669
页数：9
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