PCL库-直通滤波器

96 阅读 0 评论 64 点赞

我是靠谱客的博主乐观唇膏，这篇文章主要介绍PCL库-直通滤波器，现在分享给大家，希望可以做个参考。

一直通滤波器

直通滤波器：对指定维度（X,Y,Z,BGR等）进行某一个范围滤波，可以删除这个范围内部点，也可以删除这个范围外部的点

二关键函数

1)实例化:

pcl::PassThroughpcl::PointXYZ pass;//实例化直通滤波器

2)载入点云

pcl::PassThroughpcl::PointXYZ::setInputCloud(pcl::PointCloud<pcl::PointXYZ>::Ptr)

3)设置滤波方向

pcl::PassThroughpcl::PointXYZ::setFilterFieldName(std::string)

4)设置滤波范围

pcl::PassThroughpcl::PointXYZ::setFilterLimits(double, double)

三示例

复制代码

#include <iostream>
#include <ctime>
#include <pcl/point_types.h>
#include <pcl/filters/passthrough.h>
int main (int argc, char** argv)
{ srand(time(0));
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>);
//填入点云数据
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 = rand () / (RAND_MAX + 1.0f)-0.5;
cloud->points[i].y = rand () / (RAND_MAX + 1.0f)-0.5;
cloud->points[i].z = rand () / (RAND_MAX + 1.0f)-0.5;
}
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;
// 创建滤波器对象
pcl::PassThrough<pcl::PointXYZ> pass;//创建滤波器对象
pass.setInputCloud (cloud);
//设置待滤波的点云
pass.setFilterFieldName ("z");
//设置在Z轴方向上进行滤波
pass.setFilterLimits (0.0, 1.0);
//设置滤波范围为0~1,在范围之外的点会被剪除
//pass.setFilterLimitsNegative (true);//是否反向过滤，默认为false
pass.filter (*cloud_filtered);
//开始过滤
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;
return (0);
}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
#include <iostream>
#include <ctime>
#include <pcl/point_types.h>
#include <pcl/filters/passthrough.h>
int main (int argc, char** argv)
{ srand(time(0));
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud (new pcl::PointCloud<pcl::PointXYZ>);
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud_filtered (new pcl::PointCloud<pcl::PointXYZ>);
//填入点云数据
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 = rand () / (RAND_MAX + 1.0f)-0.5;
cloud->points[i].y = rand () / (RAND_MAX + 1.0f)-0.5;
cloud->points[i].z = rand () / (RAND_MAX + 1.0f)-0.5;
}
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;
// 创建滤波器对象
pcl::PassThrough<pcl::PointXYZ> pass;//创建滤波器对象
pass.setInputCloud (cloud);
//设置待滤波的点云
pass.setFilterFieldName ("z");
//设置在Z轴方向上进行滤波
pass.setFilterLimits (0.0, 1.0);
//设置滤波范围为0~1,在范围之外的点会被剪除
//pass.setFilterLimitsNegative (true);//是否反向过滤，默认为false
pass.filter (*cloud_filtered);
//开始过滤
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;
return (0);
}