An Algorithm of Combining Delaunay TIN Models and Region Growing for Buildings Extraction

Abstract

LiDAR technology has been widely applied in remote sensing and computer vision. Aiming at drawback of inefficient filtering and then extracting methods, the algorithm of combining Delaunay TIN models and region growing is proposed for more efficient building extraction. At First, Delaunay TIN models were built on raw LiDAR points to get connection of discrete points. Based on the geometry properties of triangles which edge points are located, protrusions edge points were extracted. Then, the extracted edge points were assigned as seed points in region growing. It yielded a point set of protrusion based on triangle network connections. Finally, since the size of non-building points is usually much smaller than the building points and non-building point sets can be deleted by threshold. The algorithm extracted building points without filtering operation, the simulation results indicate that it can improve efficiency in building extraction and guarantee the accuracy in different scenarios.