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Ellipse Fitting

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Computer Vision

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Synonyms

Ellipse matching

Definition

Fit one or more ellipses to a set of image points.

Background

Fitting geometric primitives to image data is a basic task in pattern recognition and computer vision. The fitting allows reduction and simplification of image data to a higher level with certain physical meanings. One of the most important primitive models is ellipse, which, being a projective projection of a circle, is of great importance for a variety of computer vision-related applications.

Ellipse fitting methods can be roughly divided into two categories: least square fitting and voting/clustering. Least square fitting, though usually fast to implement, requires the image data presegmented and is sensitive to outliers. On the other hand, voting techniques can detect multiple ellipses at once and exhibit some robustness against noise but suffer from a heavier computational and memory load. Furthermore, most of standard ellipse-fitting methods cannot be directly used in real-world...

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References

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Author information

Authors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, P. R. China

    Zhi-Yong Liu

Authors
  1. Zhi-Yong Liu
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Corresponding author

Correspondence to Zhi-Yong Liu .

Editor information

Editors and Affiliations

  1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

    Katsushi Ikeuchi

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© 2014 Springer Science+Business Media New York

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Liu, ZY. (2014). Ellipse Fitting. In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_318

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