Feature extraction and terrain matching

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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