A study on algorithm to extract stone tool surfaces from measured point clouds of joining materials based on images

Abstract

Stone tools were created and used for daily life during the Paleolithic and Jomon periods. Excavated stone tools and flakes are joined together to recreate the mother rock, and are referred to as a joining material. By analyzing the joining materials and reproducing the stone tool manufacturing process, various information such as the stone tool maker’s manufacturing intentions, behaviors, technical abilities, and living ranges can be obtained. Conventionally, the created joining materials were recorded with photographs and scale drawings. In recent years, as a more accurate and stable method, recording based on three-dimensional point clouds using 3D scanners has also been performed. Unfortunately, these types of measurements can obtain only outer flake surfaces of the joining material, which means the stone tools inside the joining material are hardly recognized. To obtain the assembly order of flakes and the spatial posture of the stone tools from the measured outer point clouds, it is necessary to identify each stone tool by recognizing outer flake surfaces by segmentation of surface point clouds. In this paper, we propose a method to segment each stone tool from surface point clouds obtained by 3D-measured joining materials.