ENHANCED DIRECT LEAST SQUARE FITTING OF ELLIPSES

Autor:	E.S. Maini
Rok vydání:	2006
Předmět:	Mathematical optimization business.industry Machine vision Computation Minimization problem Ellipse Hyperbola Artificial Intelligence Fixed time Conic section Robustness (computer science) Computer Vision and Pattern Recognition Artificial intelligence business Algorithm Software Mathematics
Zdroj:	International Journal of Pattern Recognition and Artificial Intelligence. 20:939-953
ISSN:	1793-6381 0218-0014
DOI:	10.1142/s021800140600506x
Popis:	This paper presents a robust and direct algorithm for the least-square fitting of ellipses to scattered data. The proposed algorithm makes use of well-known techniques that improve the robustness of the direct least-square fitting with a modest increase of the computational burden. Furthermore, by trivial modifications of the constrained minimization problem the algorithm may be converted to perform the specific fitting of other types of conics such as hyperbola. The method is simple and accurate and can be implemented with fixed time of computation. These characteristics coupled to its robustness and specificity makes the algorithm well-suited for applications requiring real-time machine vision.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::76676eea9562afd8d75866e5e2dacfd6 https://doi.org/10.1142/s021800140600506x Zobrazit plný text záznamu