Filtering of PCL

Pass through filtering

Pass through filtering preserves points within a specified range .

#include <iostream>
#include <pcl/point_types.h>
#include <pcl/filters/passthrough.h>

int main(int argc, char **argv)
{
    
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>);

    // Fill in the cloud data
    cloud->width = 5;
    cloud->height = 1;
    cloud->points.resize(cloud->width * cloud->height);

    for (auto &point : *cloud) // Fill the point cloud 
    {
    
        point.x = 1024 * rand() / (RAND_MAX + 1.0f);
        point.y = 1024 * rand() / (RAND_MAX + 1.0f);
        point.z = 1024 * rand() / (RAND_MAX + 1.0f);
    }
    cloud->points[0].z = 1;// To test the boundary conditions 
    cloud->points[1].z = 0;

    std::cerr << "Cloud before filtering: " << std::endl;
    for (const auto &point : *cloud)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    // Create the filtering object
    // Set the filter object 
    pcl::PassThrough<pcl::PointXYZ> pass;
    pass.setInputCloud(cloud);    // Enter the point cloud 
    pass.setFilterFieldName("z"); // Filter field 
    // It's only reserved here  0.0 < z < 1.0 Point cloud of 
    pass.setFilterLimits(0.0, 1.0); // Set the range of filter fields 
    //setFilterLimitsNegative The default setting is false. If you set true, said setFilterLimits Filter out the points in the range 
    //pass.setFilterLimitsNegative (true);
    pass.filter(*cloud_filtered); // filtering , And output to the cloud_filtered, But the input cloud No change 

    std::cerr << "Cloud before filtering:cloud " << std::endl;
    for (const auto &point : *cloud)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    std::cerr << "Cloud after filtering: cloud_filtered" << std::endl;
    for (const auto &point : *cloud_filtered)
        std::cerr << " " << point.x << " "
                  << point.y << " "
                  << point.z << std::endl;

    return (0);
}

Sampling under voxel filtering

#include <iostream>
#include <pcl/filters/voxel_grid.h>// Voxel filter header file 
#include <pcl/io/pcd_io.h> //PCD  Read and write class related header files 
#include <pcl/point_types.h> // Point type related definitions 
#include <pcl/visualization/cloud_viewer.h> // Point cloud visualization related definitions   Visual support header file 
#include <pcl/common/common.h> //common modular ,common.h The functions of are pcl::getMinMax3D 
int main (int argc, char** argv)
{
    
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>());
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered(new pcl::PointCloud<pcl::PointXYZ>());
  //  Fill in point cloud data 
    pcl::PCDReader reader;
  //  Change the path to the path where you store your files 
 
    reader.read ("D:\\pclcode\\filter\\voxel_grid\\source\\table_scene_lms400.pcd", *cloud); // Read the folder table_scene_lms400.pcd Point cloud file 
 
  //pcl::visualization::CloudViewer viewer("cloud viewer");// Show 
  //viewer.showCloud(cloud);// Show cloud
  std::cerr << "PointCloud before filtering: " << cloud->width * cloud->height
	  << " data points (" << pcl::getFieldsList(*cloud) << ").";// Output the total number of points before filtering 
  //system("pause");// Pause 
  //  Create filter object 
  pcl::VoxelGrid<pcl::PointXYZ> sor;// Create filter object 
  sor.setInputCloud (cloud);// Set the input point cloud 
  sor.setLeafSize (0.01f, 0.01f, 0.01f);// The voxel size is set to 10*10*10cm
  sor.filter (*cloud_filtered);// Perform filtering , Save the filter results in cloud_filtered
  std::cerr << "PointCloud after filtering: " << cloud_filtered->width * cloud_filtered->height 
       << " data points (" << pcl::getFieldsList (*cloud_filtered) << ").";// Output the total number of filtered 
  pcl::PCDWriter writer;//pcd Write operations 
  writer.write ("2f.pcd", *cloud_filtered);// Store the filtered point cloud in build Folder , And named it 2f.pcd
  //pcl::visualization::CloudViewer viewer("cloud viewer");// Show 
  //viewer.showCloud(cloud_filterd);// Show cloud
  system("pause");// Pause 
  return (0);
}
//PointCloud before filtering : 460400 data points(x y z).
//PointCloud after filtering : 41049 data points(x y z).
// Please press any key to continue . . .