DocumentCode :
2617181
Title :
Optimal contour approximation by deformable piecewise cubic splines
Author :
Liu, Linnan ; Schunck, Brian G. ; Meyer, Charles R.
Author_Institution :
Michigan Univ., Ann Arbor, MI, USA
fYear :
1991
fDate :
3-6 Jun 1991
Firstpage :
638
Lastpage :
643
Abstract :
An optimal deformable contour approximation algorithm using a cardinal-form piecewise cubic spline (PCS) curve representation is presented. The approximation is optimal in the sense of least square errors in both location and orientation. The knots are set automatically at high curvature positions. The sample data are generated by a robust edge fragment detection algorithm which is optimal in the sense of a weighted absolute error. An initial contour placement algorithm uses a penalized maximum likelihood algorithm to group the edge fragments together for an initial contour. A controlled deformable contour algorithm refines the initial contour to cover meaningful edge features
Keywords :
computer vision; curve fitting; optimisation; splines (mathematics); cardinal-form piecewise cubic spline; contour placement algorithm; deformable piecewise cubic splines; edge detection; edge features; edge fragments; high curvature positions; knots; object boundary estimation; optimal deformable contour approximation algorithm; penalized maximum likelihood algorithm; robust edge fragment detection algorithm; weighted absolute error; Approximation algorithms; Computer vision; Curve fitting; Data mining; Image edge detection; Least squares approximation; Maximum likelihood estimation; Personal communication networks; Robustness; Surface fitting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
Conference_Location :
Maui, HI
ISSN :
1063-6919
Print_ISBN :
0-8186-2148-6
Type :
conf
DOI :
10.1109/CVPR.1991.139767
Filename :
139767
Link To Document :
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