Based On The Principle Of Mathematical Morphology And Terrascan Lidar Point Cloud Data Classification

Lidar system can quickly access the real-time three-dimensional ground information with high-precision; Lidar has active scanning models, which enable it to work all-day time without being affected by weather. At the same time. Lidar data and the related products can facilitate a connection with various softwares, such as CAD, 3D animation, and so on. With those advantages, Lidar system has been growingly applied in various fields. However, the classification of the point data sets is becoming the bottleneck issue for their application and development, which accounts for 60-80 percent of the workload for the Lidar data post-processing. As a result, further research regarding the classification method is quite necessary and valuable for Lidar applications.In recent years, under the efforts of many scholars, some relative advanced methods regarding the point data sets classification have been developed gradually. At present, TerraScan is one of the most complete and practical softwares based on the classification method of Alexsson. In this paper, the point data samples are classified by both TerraScan and the classification method based on the principle mathematical morphology. Additionally, in order to evaluate the advantages and disadvantages of the classification method, the results based on the two classification method are compared, and its further application and development have been evaluated.Those seven experimental point data sets used in this paper are provided by ISPRS, with various sorts of typical topographical characters. Besides, there are artifical reference samples data in these seven regions that can be used to have quantificational evaluation of the final classification results.The main research works include:(1) The introduction of the workflow, operational interfaces and the determination of the parameters during classification using TerraScan. With this software, seven experimental data sets are classified. (2) The classification method based on the principle of mathematical morphology is applied to classify the experimental data sets by using Matlab. The choosing of the operation window sizes is the key process to classify different kinds of non-ground points.(3) The accuracy assessment and contrastive analysis of the classification results with the two classification methods.Results show that the classification accuracy of the method based on the principle of mathematical morphology is comparable with that of TerraScan. Its operational principle and procedures are much easier. It has very promising application future.