{"title":"进一步五点配合椭圆拟合","authors":"Paul L. Rosin","doi":"10.1006/gmip.1999.0500","DOIUrl":null,"url":null,"abstract":"<div><p>The least-squares method is the most commonly used technique for fitting an ellipse through a set of points. However, it has a low breakdown point, which means that it performs poorly in the presence of outliers. We describe various alternative methods for ellipse fitting which are more robust: the Theil–Sen, least median of squares, Hilbert curve, and minimum volume estimator approaches. Testing with synthetic data demonstrates that the least median of squares is the most suitable method in terms of accuracy and robustness.</p></div>","PeriodicalId":100591,"journal":{"name":"Graphical Models and Image Processing","volume":"61 5","pages":"Pages 245-259"},"PeriodicalIF":0.0000,"publicationDate":"1999-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1006/gmip.1999.0500","citationCount":"80","resultStr":"{\"title\":\"Further Five-Point Fit Ellipse Fitting\",\"authors\":\"Paul L. Rosin\",\"doi\":\"10.1006/gmip.1999.0500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The least-squares method is the most commonly used technique for fitting an ellipse through a set of points. However, it has a low breakdown point, which means that it performs poorly in the presence of outliers. We describe various alternative methods for ellipse fitting which are more robust: the Theil–Sen, least median of squares, Hilbert curve, and minimum volume estimator approaches. Testing with synthetic data demonstrates that the least median of squares is the most suitable method in terms of accuracy and robustness.</p></div>\",\"PeriodicalId\":100591,\"journal\":{\"name\":\"Graphical Models and Image Processing\",\"volume\":\"61 5\",\"pages\":\"Pages 245-259\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1006/gmip.1999.0500\",\"citationCount\":\"80\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Graphical Models and Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1077316999905002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Graphical Models and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077316999905002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The least-squares method is the most commonly used technique for fitting an ellipse through a set of points. However, it has a low breakdown point, which means that it performs poorly in the presence of outliers. We describe various alternative methods for ellipse fitting which are more robust: the Theil–Sen, least median of squares, Hilbert curve, and minimum volume estimator approaches. Testing with synthetic data demonstrates that the least median of squares is the most suitable method in terms of accuracy and robustness.