Automatic building roof segmentation based on PFICA algorithm and morphological filtering from LiDAR point clouds

Abstract

In this study, we propose a new approach for segmenting building roofs from Light Detection And Ranging (LiDAR) point clouds. The algorithm takes advantage of height gradients to automatically seed Purposive FastICA (PFICA) algorithm. The PFICA algorithm with a novel seeding method is implemented to detect ridge points from point clouds of building roofs. Then, 2D coordinates are used to rasterize the detected points. Eventually, morphological filtering and thinning algorithms are used to extract inner and external boundaries of the building roofs. In addition, the potential of PFICA algorithm in clustering 3D point clouds are discussed. The results obtained on a set of LiDAR point clouds demonstrat