Referenced Items are not available for this document.
In the literature, methods for fitting superellipses to data tend to be computationally expensive due to the nonlinear nature of the problem. This paper describes and tests several fitting techniques which provide different trade-offs between efficiency and accuracy. In addition, we describe various alternative error of fit measures that can be applied by most superellipse fitting methods
Published in:
Pattern Analysis and Machine Intelligence, IEEE Transactions on
(Volume:22
,
Issue:
7
)
Date of Publication: Jul 2000
- Page(s):
- 726 - 732
- ISSN :
- 0162-8828
- INSPEC Accession Number:
- 6718571
- Digital Object Identifier :
- 10.1109/34.865190
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Jul 2000
- Sponsored by :
- IEEE Computer Society
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