PCL中使用直通滤波器对点云进行滤波处理

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我是靠谱客的博主舒心纸飞机，这篇文章主要介绍PCL中使用直通滤波器对点云进行滤波处理，现在分享给大家，希望可以做个参考。

#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 (size_t i = 0; i < cloud->points.size(); ++i)
{
cloud->points[i].x = 1024 * rand() / (RAND_MAX + 1.0f);
cloud->points[i].y = 1024 * rand() / (RAND_MAX + 1.0f);
cloud->points[i].z = 1024 * rand() / (RAND_MAX + 1.0f);
}

std::cerr << "Cloud before filtering: " << std::endl;
for (size_t i = 0; i < cloud->points.size(); ++i)
std::cerr << " " << cloud->points[i].x << " "
<< cloud->points[i].y << " "
<< cloud->points[i].z << std::endl;

// Create the filtering object
pcl::PassThrough<pcl::PointXYZ> pass;
pass.setInputCloud(cloud);
pass.setFilterFieldName("z");
pass.setFilterLimits(100.0, 400.0);
//pass.setFilterLimitsNegative (true);
//pass.setNegative(true);
pass.filter(*cloud_filtered);

std::cerr << "Cloud after filtering: " << std::endl;
for (size_t i = 0; i < cloud_filtered->points.size(); ++i)
std::cerr << " " << cloud_filtered->points[i].x << " "
<< cloud_filtered->points[i].y << " "
<< cloud_filtered->points[i].z << std::endl;
system("pause");
return (0);
}