DocumentCode :
2992302
Title :
Surface classification: hypothesis testing and parameter estimation
Author :
Flynn, P.J. ; Jain, A.K.
Author_Institution :
Dept. of Comput. Sci., Michigan State Univ., East Lansing, MI, USA
fYear :
1988
fDate :
5-9 Jun 1988
Firstpage :
261
Lastpage :
267
Abstract :
A 3-D surface classification method based on the quadric surface model is described. This technique does not require the points from the surface to lie on a grid. A sample of surface points is classified as planar or nonplanar through two hypothesis tests. If the sample is nonplanar, curvature features are evaluated at each point to classify the sample as spherical, cylindrical, or conical. A nonlinear optimization technique is then used to refine the parameters (e.g. radius, orientation) of the resulting surface type
Keywords :
optimisation; parameter estimation; pattern recognition; 3-D surface classification; nonlinear optimization; pattern recognition; quadric surface model; Computer science; Computer vision; Data mining; Equations; Image segmentation; Manufacturing; Parameter estimation; Pixel; Surface fitting; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Conference_Location :
Ann Arbor, MI
ISSN :
1063-6919
Print_ISBN :
0-8186-0862-5
Type :
conf
DOI :
10.1109/CVPR.1988.196246
Filename :
196246
Link To Document :
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