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ID 19958
Eprint ID
19958
フルテキストURL
著者
金谷 健一 Department of Computer Science Okayama University
Rangrajan Prasanna Department of Electrical Engineering Southern Methodist University
抄録
This paper presents a new method for fitting an ellipse to a point sequence extracted from images. It is widely known that the best fit is obtained by maximum likelihood. However, it requires iterations, which may not converge in the presence of large noise. Our approach is algebraic distance minimization; no iterations are required. Exploiting the fact that the solution depends on the way the scale is normalized, we analyze the accuracy to high order error terms with the scale normalization weight unspecified and determine it so that the bias is zero up to the second order. We demonstrate by experiments that our method is superior to the Taubin method, also algebraic and known to be highly accurate.
発行日
2010-01
出版物タイトル
Memoirs of the Faculty of Engineering, Okayama University
出版物タイトル(別表記)
岡山大学工学部紀要
44巻
出版者
Faculty of Engineering, Okayama University
出版者(別表記)
岡山大学工学部
開始ページ
42
終了ページ
49
ISSN
1349-6115
NCID
AA12014085
資料タイプ
紀要論文
言語
English
論文のバージョン
publisher
査読
無し
Eprints Journal Name
mfe