Journal of Theoretical and Applied Information Technology
Recently, many applications require 3D information of an object (i.e. point cloud) such as 3D image scanning, 3D surface reconstruction and etc. However many researches on point cloud registration face many challenges especially for increasing the accuracy of point cloud matching. This research employs surface curvature features in discrete surfaces. A surface curvature feature is a pointer of ridges that are invariant to rigid body transformations. In this paper, a new algorithm of point cloud registration for non-deformable object is proposed. This algorithm employs surface curvature features estimated by fitting nearest neighbor of local point to hyperbolic paraboloid equation.