Streamlined Compression Analysis And Practice Of Point Cloud Data Based On Coordinate Increment

3D laser scanning technology is a new research hot spot in the field of surveying andmapping engineering at present. Three-dimensional laser scanner is one of the important toolsfor reverse engineering modeling at the same time, is widely used in computer vision, medicalscience, industrial manufacturing, civil engineering applications and other fields. The key of3D laser scanning technology application is: Getting the point cloud data of the target surfaceis first, and then process these point cloud data, and finally obtain the final results. In thispaper, a more in-depth study of the basic theories and methods about3D laser scanningtechnology and data processing, in particular data processing theory streamline compressionexperiments carried out more detailed studies.Firstly, the background and significance of the study of this subject, status andapplications of3D laser scanning technology is introduced, then it discusses the compositionof the three-dimensional laser scanning system in detail, and how it works, and thethree-dimensional laser scanning system error made specific analysis. By analyzing andprocessing point cloud data summarizes the characteristics of the scanned point cloud data,and then focuses on the data in a simplified data processing point cloud to streamline severaltypical compression methods, including random sampling method, bounding boxes, regionalgravity compression method and the curvature of the sampling method. On this basis, a newmethod based on incremental streamline coordinate compression is raised. In order to timely,quickly acquired the data processing, combined with MATLAB language compressed datacorresponding to streamline procedures, based on the above algorithm programming presentsa simple and practical new approach-based on incremental coordinates streamlinecompression algorithm. First combine scanned point cloud data field experiment wasconducted to verify the feasibility of this method. Finally, the above method with regional gravity compression method, conducted experiments comparing the advantages anddisadvantages of various methods of sampling and curvature their respective applicationconditions.Innovation of this paper:(1) proposed streamlining compression algorithm based onincremental coordinate and verify its feasibility;(2) on the MATLAB soft realization of atypical point cloud data reduction compression algorithm;(3) point cloud data analysisalgorithms to streamline compression applications, focusing on the compression algorithm todo a comparative analysis.