Using Gradient Orientation to Improve Least Squares Line Fitting (CROSBI ID 610373)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Petković, Tomislav ; Lončarić, Sven
engleski
Using Gradient Orientation to Improve Least Squares Line Fitting
Straight line fitting is an important problem in computer and robot vision. We propose a novel method for least squares line fitting that uses both the point coordinates and the local gradient orientation to fit an optimal line by minimizing the proposed algebraic distance. The proposed inclusion of gradient orientation offers several advantages: (a) one data point is sufficient for the line fit, (b) for the same number of points the fit is more precise due to inclusion of gradient orientation, and (c) outliers can be rejected based on the gradient orientation or the distance to line.
line fitting; line normal; image gradient
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Podaci o prilogu
226-231.
2014.
objavljeno
Podaci o matičnoj publikaciji
Conference on Computer and Robot Vision CRV 2014
Juan E. Guerrero
Montréal: Institute of Electrical and Electronics Engineers (IEEE)
78-1-4799-4338-8
Podaci o skupu
Conference on Computer and Robot Vision
poster
06.05.2014-09.05.2014
Montréal, Kanada