Feature extraction and terrain matching
Goldgof, D.B.
Huang, T.S.
Lee, H.
Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL;
This paper appears in: Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Publication Date: 5-9 Jun 1988
On page(s): 899-904
Meeting Date: 06/05/1988 - 06/09/1988
Location: Ann Arbor, MI, USA
ISBN: 0-8186-0862-5
References Cited: 13
INSPEC Accession Number: 3258588
Digital Object Identifier: 10.1109/CVPR.1988.196339
Current Version Published: 2002-08-06
Abstract
An algorithm is presented which uses Gaussian curvature for
extracting special points on the terrain, and then uses these points for
recognition of particular regions of the terrain. The Gaussian curvature
is chosen because it is invariant under isometry, which includes
rotation and translation. In the Gaussian curvature image, the points of
maximum and minimum curvature are extracted and used for matching. The
stability of the position of these points in the presence of noise with
resampling is investigated. The Gaussian curvature is calculated from
the 3-D digital terrain data by fitting a quadratic surface over a
square window and calculating directional derivatives of this surface. A
method of surface fitting which is invariant to coordinate system
transformation is suggested and implemented. This method involves
finding an optimal directional in which the fitting is performed
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