Feature Extraction for Illustrating 3D Stone Tools from Unorganized Point Clouds

This paper presents a method for extracting features for illustrating stone tools. Features are detected from unorganized point clouds obtained by a 3D laser scanner. The curvature of each point in the point clouds is estimated by local surface fitting algorithm and used for detecting potential feature points. Feature lines are extracted by directionally growing algorithm. The main idea of our method is to extract feature lines using principal curvatures and principal directions of the potential feature points along the axis directions and to merge all extracted lines. The detected features are modified by specific knowledge on illustrating stone tools.