关键词: 机载激光雷达测量, 建筑物轮廓提取, 区域生长算法, 三维霍夫变换, α-shape算法

Abstract: As an important element of 3D reconstruction of buildings, building contours are crucial in building smart cities and digital cities. Aiming at some problems in the extraction of point cloud filtering, building roof surface extraction, building contour extraction and extraction accuracy evaluation from the airborne LiDAR point cloud, this paper proposes a comprehensive region growth improvement algorithm, three-dimensional Hough transform algorithm and α-shape algorithm for building contour extraction method. Based on the denoising of airborne LiDAR point cloud data, the method uses an improved region growing algorithm to filter the ground points and removes the lower height features through the height threshold based on the normalized elevation features of the ground point to the ground. Then, based on the three-dimensional Hough transform algorithm, the building plane is extracted from the remaining buildings and the tall tree point cloud, and finally the contour information of the building is extracted using the α-shape algorithm. The point cloud data of a certain urban area scanned by the RIEGLVQ-1560i airborne LiDAR measurement system is calculated, and the accuracy of the extracted building outline is evaluated by the evaluation indexes such as matching degree, shape similarity and positional accuracy. The results show that the integrated region growth improvement algorithm, three-dimensional Hough transform algorithm and α-shape algorithm for building contour extraction method can accurately extract the contour information of buildings, and have the characteristics of stability and universal applicability for wide-area building contour extraction.

Key words: airborne LiDAR point cloud, building contour extraction, region growing, Hough transform, α-shape algorithm