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
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;
Conference_Titel :
Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Conference_Location :
Ann Arbor, MI
Print_ISBN :
0-8186-0862-5
DOI :
10.1109/CVPR.1988.196246