PRIMITIVE SEGMENTATION OF DOUGONG COMPONENTS BASED ON REGIONAL CLUSTERING

Abstract. As one of the most characteristic components of ancient Chinese architecture, Dougong has an important significance in the history of ancient Chinese architecture, but with the passage of time, wooden building components are prone to decay and missing, so it is particularly important to digitally retain the Dougong. In order to realize the Dougong component segmentation, this paper proposes a super voxel-based Dougong component primitive segmentation method, which is divided into two parts: firstly, super voxelizing the Dougong point cloud data, and secondly, realizing the Dougong component primitive segmentation by using multi-geometric constrained region growth algorithm. In order to verify the effectiveness of the method, this paper selects three main Dougong types of the Qing Dynasty, including pingshenke, jiaoke, zhutouke, for experimental validation, and the results show that the combination of super voxel and regional growth algorithm can effectively extract the geometric primitive surface of the Dougong components with high extraction efficiency and good adaptability, which can be prepared for the subsequent knowledge of Dougong construction method to achieve component segmentation.