Building contour extraction method based on point cloud
Studying how to quickly and accurately extract building information is of great significance for urban construction,development,and management. Based on three-dimensional (3D) point cloud data,this paper studied and implemented the extraction of geometric information from buildings. The idea of building information extraction in this paper was as follows:firstly,to reduce the amount of point cloud data and improve the subsequent algorithm operation speed,the slope filtering algorithm was improved and applied to the classification of ground and non-ground points in the point cloud,so as to extract non-ground points. Secondly,an improved 3D Hough transform (HT) was proposed to extract building elevation points. Finally,a dimensionality reduction-based boundary index method was used to determine the building contour lines and extract local features. The experimental results using measured 3D point cloud data show that in complex point cloud spatial scenes,the proposed method can effectively avoid interference such as noise points,efficiently and accurately extract building contours and local features,and provide positive technical support for smart city construction,urban planning and construction,and other fields.
three-dimensional (3D) point cloudpoint cloud filteringbuilding contourlocal featuresimproved 3D Hough transform algorithm