关键词: 点云数据；机器学习；典型路面特征；自动化提取

Abstract: In order to extract road elements from point cloud data and provide a basis for the digitization of road infrastructure and the production of high-precision maps, an automatic extraction process is developed in this paper by combining ground segmentation and pavement extraction. Firstly, the ground segmentation is carried out, and the algorithm is used to preprocess the point cloud data to realize the effective separation of the ground point cloud and the non-ground point cloud. Secondly, the seed points are selected, and the seed points representing the typical pavement characteristics are selected based on the intelligent algorithm of the geometric characteristics of the point cloud. Finally, the regional growth algorithm is used to automatically extract the pavement, which solves the problem of over-segmentation of the growth algorithm.

Key words: point cloud date; machine learning; typical pavement characteristics; automatic extraction