Combined filtering algorithm for vehicle-mounted laser point cloud
Traditional vehicle-mounted point cloud filtering algorithms are unable to effectively remove non-ground points in areas with large terrain slopes.To solve this problem,this paper analyzed the characteristics of the cloth simulation filtering(CSF)algorithm and the traditional triangular irregular network(TIN)and proposed an improved TIN filtering algorithm based on the CSF algorithm.Firstly,the CSF algorithm was used to filter the original point cloud,and initial ground points were obtained.Secondly,the improved TIN filtering algorithm was used to further filter the results filtered by the CSF algorithm.Neighborhood convolution was utilized to select seed points and construct virtual seed points,and the grid size was changed according to the number of filtering times for iterative filtering.Two sets of urban road point clouds with different terrain conditions were used for experiments,and the filtering results of different filtering algorithms were compared.The results show that the combined filtering algorithm proposed in this paper can effectively compensate for the shortcomings of a single filtering algorithm and can better adapt to urban conditions.
point cloud filteringcloth simulation filteringimproved irregular triangular networksgridaccuracy inspection
国家科技期刊平台
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