A classification method for building detection based on LiDAR point clouds

Building detection using LiDAR data is a popular topic in LiDAR data processing. The object classification can play an important role in the detection. In this paper, a new algorithm based on LiDAR point clouds is developed to resolve the object classification difficulties in the case of trees close to buildings. Compared with other algorithms, the methods can work effectively due to use the combination of height texture and regular geometric element. The experiment results is also given and discussed to improve the validity of the proposed algorithm.