Feature Line Extraction of Stone Tools Based on Mahalanobis Distance Metric

Abstract

Point-cloud-based technique plays a very significant role in 3D model restoration. In the archaeological application of stone tools, the scale drawing, which is hand-drawn from measured stone tools, is traditionally used. In the scale drawing creation, a base drawing which consists outline and ridge lines is initially drawn from geometric features of shape. After that other lines are extracted from knowledge of making stone tools and are added to the base drawing. It requires special knowledge to extract feature lines from stone tools so that scale drawing is time-consuming. Therefore, if the base drawing is automatically extracted, the working hours are reduced. To overcome this issue, this paper proposes a feature line extraction method using the Mahalanobis distance metric. First, the points on outline are extracted from a point cloud. Then, the surface variation is calculated with a various number of neighbors and thus the potential feature points are detected by the analysis of its surface variation. After that, the potential feature points are thinned towards the highest variation points by using Laplacian smoothing. Then, the thinned feature points are shrunk to the potential feature points. Finally, a feature line is extracted by connecting the nearest thinned feature points locating in the Mahalanobis distance field. To verify our method, the extracted feature lines are compared to the ground truth of base drawing drawn by archaeological illustrators. Our method is applied to stone tools, and we confirm the effectiveness of our method.