Research On Simplified Algorithm Of 3D Point Cloud Data Based On Grey Wolf Optimized K-means Clustering Algorithm

With the rapid development of computer technology and the continuous updating of 3D laser scanning equipment,the acquisition of 3D point cloud data is more convenient and fast,so that a large amount of 3D point cloud data has emerged.As far as a single 3D point cloud model is concerned,its data volume can also reach tens of thousands or even tens of millions.Too large point cloud data not only brings great challenges to its storage,transmission and display,but also brings inconvenience to later point cloud modeling or drawing rendering.Thus,3D point cloud data simplification technology came into being.Simplifying the 3D point cloud data can promote the development of the 3D digital film and television,3D animation and game industries.At the same time,it can complement each other with 3D object modeling,hole repair,3D object stitching and point cloud registration.This paper makes in-depth research on the 3D point cloud data simplification algorithm.The specific research content is summarized as follows:(1)A k-means clustering algorithm based on grey wolf optimization is proposed.The grey wolf optimization algorithm is used to improve the k-means clustering algorithm.Through the ? wolf,? wolf and ? wolf first three superior wolf wolves,iteratively optimizes and updates the position of the candidate ? wolf,and then,in turn,continuously updates the first three superior wolf,and finally obtains the optimal clustering center.Experiments on 4 types of UCI data sets verify the feasibility and effectiveness of the improved k-means clustering algorithm;(2)A simplified algorithm of 3D point cloud data based on k-means clustering optimized by grey wolf is proposed.Use the improved k-means clustering algorithm to classify the 3D point cloud data,and then fit the point cloud data in each cluster to form a curved surface.And for each point in the point cloud data,calculate the root mean square curvature of the point,then solve for the average value of the root mean square curvature of all points,and finally compare them.In this way,the redundant points are deleted,and the purpose of simplifying the 3D point cloud data is achieved.Analyze and compare the results obtained from the experiment with the simplified results of other simplified algorithms,andsummarize the advantages and disadvantages of the proposed simplified algorithms;(3)Design and development of point cloud simplification and drawing display system,using Microsoft Visiual C ++ 6.0,OpenGL and PCL libraries.The system realize the import and export of 3D point cloud data,the basic operation of 3D point cloud data,the simplified operation of 3D point cloud data,the drawing and display functions of 3D point cloud data and other functions.