Abstract
Accurate and consistent methods are required to reconstruct the surface of an object from a set of points, which are located on the surface of the object. The detection and generation of feature lines appearing on the surface is considered to be an attractive preprocessing step before the surface reconstruction process. In this paper, the authors propose a method to detect feature lines from point clouds. The detection and generation process depends on a number of effective parameters. The authors have identified four effective parameters for feature line generation: 1) the number k nearest neighbors, 2) curvature value, 3) cycle length and 4) minimum length of short branches. The efficiency of the detection by finding the parameter values that closely match the existing feature lines are examined through test problems of point clouds. Finally, the effectiveness of the method is evaluated by application to a remote sensed point data set representing topographic features of the Jordan valley.
