Three Dimensional Laser Scanning Point Cloud Denoising And Its Application In Modeling

The application of 3D laser scanning technology in obtaining spatial data is more and more widely.When using 3D laser scanning technology to obtain the point cloud data,due to the observation condition,the equipment itself and the influence of the external environment condition,some noise points will be scanned.In 3D modeling,it is necessary to denoise the point cloud data so as to improve the accuracy of the 3 D model.On the basis of studying the shortcomings of the existing methods for noise classification and noise processing of point cloud data,this paper proposes a point cloud data denoising algorithm based on barycenter.The algorithm is improved on the basis of bounding point cloud data compression algorithm.The technology flow of the algorithm is clear,the algorithm is reliable,and it is easy to implement by MATLAB programming..At the same time,in order to compare the denoising effect of the algorithm,a matlab program is developed to increase the random noise of point cloud.Two objects were selected for three-dimensional laser scanning.After preprocessing the cloud data,we add a certain amount of random noise by this program,and use this algorithm and program to deal with the point cloud data with increased random noise.The experimental results show that the point cloud data denoising algorithm based on barycenter is obviously effective in removing random noise,and the program runs correctly.The denoising algorithm of this paper and the denoising method of Geomagic Studio software are used to denoise and model the point cloud data.The experimental results show that the accuracy of the model obtained by the two methods is equivalent.The precision of modeling after denoising is better than that of denoising,which shows that the algorithm is effective in modeling.Using this algorithm to model is similar to the effectiveness of professional software and has a certain practical value.