PCL点云库学习笔记（4）：区域生长点云分割

初学者笔记：

点云数据链接：
链接：https://pan.baidu.com/s/1VTVxn3BntbAr9tGHv6L-HA
提取码：u81q

代码：

#include 
VTK_MODULE_INIT(vtkRenderingOpenGL)
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include
#include
#include 
#include 

using namespace pcl;
using namespace std;
typedef PointXYZ PoinT;
int *rand_rgb(){//随机产生颜色
	int *rgb = new int[3];
	rgb[0] = rand() % 255;
	rgb[1] = rand() % 255;
	rgb[2] = rand() % 255;
	return rgb;
}
int main(){
	PointCloud::Ptr cloud(new PointCloud);
	if (io::loadPCDFile("C:\\Users\\Administrator\\Desktop\\desk.pcd", *cloud) == -1){
		PCL_ERROR("read false");
	}
	//降采样****************************************************
	VoxelGrid vox;
	PointCloud::Ptr vox_cloud(new PointCloud);
	vox.setInputCloud(cloud);
	vox.setLeafSize(0.01, 0.01, 0.01);
	vox.filter(*vox_cloud);
	//去噪声***************************************************
	StatisticalOutlierRemovalsor;
	PointCloud::Ptr sor_cloud(new PointCloud);
	sor.setInputCloud(vox_cloud);
	sor.setMeanK(20);
	sor.setStddevMulThresh(0.02);
	sor.filter(*sor_cloud);
	//法向量求解**********************************************
	NormalEstimation ne;
	search::KdTree::Ptr tree(new search::KdTree);
	PointCloud::Ptr normal_cloud(new PointCloud);
	ne.setInputCloud(sor_cloud);
	ne.setKSearch(20);
	ne.setSearchMethod(tree);
	ne.compute(*normal_cloud);
	//基于法向量和曲率的区域生长算法**************************
	PointCloud::Ptr reg_cloud(new PointCloud);
	RegionGrowing reg;
	reg.setInputCloud(sor_cloud);
	reg.setSearchMethod(tree);
	reg.setNumberOfNeighbours(20);
	reg.setMinClusterSize(50);
	reg.setMaxClusterSize(100000);
	reg.setSmoothnessThreshold(3.0 / 180 * M_PI);
	reg.setCurvatureThreshold(1.0);
	reg.setInputNormals(normal_cloud);

	vectorclusters;
	reg.extract(clusters);

	visualization::PCLVisualizer::Ptr viewer(new visualization::PCLVisualizer("Result of RegionGrowing"));
	for (int iter = 0; iter < clusters.size();iter++)
	{
		PointCloud::Ptr copy_cloud(new PointCloud);
		vector inlier = clusters[iter].indices;
		copyPointCloud(*sor_cloud, inlier, *copy_cloud);
		stringstream ss;
		ss << "C:\\Users\\Administrator\\Desktop\\" << "RegionGrowing_clouds" << iter << ".pcd";
		//io::savePCDFileASCII(ss.str(), *copy_cloud);
		int *rgb = rand_rgb();//随机生成0-255的颜色值
		visualization::PointCloudColorHandlerCustomrgb1(copy_cloud, rgb[0], rgb[1], rgb[2]);//提取的平面不同彩色展示
		delete[]rgb;
		viewer->addPointCloud(copy_cloud, rgb1, ss.str());
		viewer->setPointCloudRenderingProperties(visualization::PCL_VISUALIZER_POINT_SIZE, 3, ss.str());
	}
	viewer->spin();

	return 0;
}

可视化结果：

利用ExtractIndices按点云索引提取点云子集

#include 
VTK_MODULE_INIT(vtkRenderingOpenGL)
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace pcl;
using namespace std;
typedef PointXYZ PoinT;
int *rand_rgb(){//随机产生颜色
	int *rgb = new int[3];
	rgb[0] = rand() % 255;
	rgb[1] = rand() % 255;
	rgb[2] = rand() % 255;
	return rgb;
}
int main(){
	PointCloud::Ptr cloud(new PointCloud);
	if (io::loadPCDFile("C:\\Users\\Administrator\\Desktop\\desk.pcd", *cloud) == -1){
		PCL_ERROR("read false");
	}
	//降采样****************************************************
	VoxelGrid vox;
	PointCloud::Ptr vox_cloud(new PointCloud);
	vox.setInputCloud(cloud);
	vox.setLeafSize(0.01, 0.01, 0.01);
	vox.filter(*vox_cloud);
	//去噪声***************************************************
	StatisticalOutlierRemovalsor;
	PointCloud::Ptr sor_cloud(new PointCloud);
	sor.setInputCloud(vox_cloud);
	sor.setMeanK(20);
	sor.setStddevMulThresh(0.02);
	sor.filter(*sor_cloud);
	//法向量求解**********************************************
	NormalEstimation ne;
	search::KdTree::Ptr tree(new search::KdTree);
	PointCloud::Ptr normal_cloud(new PointCloud);
	ne.setInputCloud(sor_cloud);
	ne.setKSearch(20);
	ne.setSearchMethod(tree);
	ne.compute(*normal_cloud);
	//基于法向量和曲率的区域生长算法**************************
	PointCloud::Ptr reg_cloud(new PointCloud);
	RegionGrowing reg;
	reg.setInputCloud(sor_cloud);
	reg.setSearchMethod(tree);
	reg.setNumberOfNeighbours(20);
	reg.setMinClusterSize(50);
	reg.setMaxClusterSize(100000);
	reg.setSmoothnessThreshold(3.0 / 180 * M_PI);
	reg.setCurvatureThreshold(1.0);
	reg.setInputNormals(normal_cloud);

	vectorclusters;
	reg.extract(clusters);
	ExtractIndicesext;
	visualization::PCLVisualizer::Ptr viewer(new visualization::PCLVisualizer("Result of RegionGrowing"));
	for (int iter = 0; iter < clusters.size();iter++)
	{
	//调用方式*************************************************************
		PointCloud::Ptr final_cloud(new PointCloud);
		vector inlier = clusters[iter].indices;
		boost::shared_ptr>index = boost::make_shared>(inlier);
		ext.setInputCloud(sor_cloud);
		ext.setIndices(index);
		ext.setNegative(false);
		ext.filter(*final_cloud);
	//************************************************************************
		stringstream ss;
		ss << "C:\\Users\\Administrator\\Desktop\\" << "RegionGrowing_clouds" << iter << ".pcd";
		//io::savePCDFileASCII(ss.str(), *copy_cloud);
		int *rgb = rand_rgb();//随机生成0-255的颜色值
		visualization::PointCloudColorHandlerCustomrgb1(final_cloud, rgb[0], rgb[1], rgb[2]);//提取的平面不同彩色展示
		delete[]rgb;
		viewer->addPointCloud(final_cloud, rgb1, ss.str());
		viewer->setPointCloudRenderingProperties(visualization::PCL_VISUALIZER_POINT_SIZE, 3, ss.str());
	}
	viewer->spin();

	return 0;
}

分割线----------------------------------------------------------------------------------------------------------------------------------------
获取分割的结果，并获取剩余的点云数据
代码：

#include 
VTK_MODULE_INIT(vtkRenderingOpenGL)
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 
#include 

using namespace pcl;
using namespace std;
typedef PointXYZ PoinT;
int *rand_rgb(){//随机产生颜色
	int *rgb = new int[3];
	rgb[0] = rand() % 255;
	rgb[1] = rand() % 255;
	rgb[2] = rand() % 255;
	return rgb;
}
int main(){
	PointCloud::Ptr cloud(new PointCloud);
	if (io::loadPCDFile("C:\\Users\\Administrator\\Desktop\\desk.pcd", *cloud) == -1){
		PCL_ERROR("read false");
	}
	//降采样****************************************************
	VoxelGrid vox;
	PointCloud::Ptr vox_cloud(new PointCloud);
	vox.setInputCloud(cloud);
	vox.setLeafSize(0.01, 0.01, 0.01);
	vox.filter(*vox_cloud);
	//去噪声***************************************************
	StatisticalOutlierRemovalsor;
	PointCloud::Ptr sor_cloud(new PointCloud);
	sor.setInputCloud(vox_cloud);
	sor.setMeanK(20);
	sor.setStddevMulThresh(0.02);
	sor.filter(*sor_cloud);
	//法向量求解**********************************************
	NormalEstimation ne;
	search::KdTree::Ptr tree(new search::KdTree);
	PointCloud::Ptr normal_cloud(new PointCloud);
	ne.setInputCloud(sor_cloud);
	ne.setKSearch(20);
	ne.setSearchMethod(tree);
	ne.compute(*normal_cloud);
	//基于法向量和曲率的区域生长算法**************************
	PointCloud::Ptr reg_cloud(new PointCloud);
	RegionGrowing reg;
	reg.setInputCloud(sor_cloud);
	reg.setSearchMethod(tree);
	reg.setNumberOfNeighbours(20);
	reg.setMinClusterSize(50);
	reg.setMaxClusterSize(100000);
	reg.setSmoothnessThreshold(3.0 / 180 * M_PI);
	reg.setCurvatureThreshold(1.0);
	reg.setInputNormals(normal_cloud);

	vectorclusters;
	reg.extract(clusters);
	ExtractIndicesext;
	visualization::PCLVisualizer::Ptr viewer(new visualization::PCLVisualizer("Result of RegionGrowing"));
	vectorindex;
	for (int iter = 0; iter < clusters.size();iter++)
	{
		//将索引汇总************************************************************************
		PointCloud::Ptr final_cloud(new PointCloud);
		vector inlier = clusters[iter].indices;
		index.insert(index.end(), inlier.begin(), inlier.end());
		//提取每个索引对应得点云并展示*******************************************************
		boost::shared_ptr>index1 = boost::make_shared>(inlier);
		ext.setInputCloud(sor_cloud);
		ext.setIndices(index1);
		ext.filter(*final_cloud);
		stringstream ss;
		ss << "C:\\Users\\Administrator\\Desktop\\" << "RegionGrowing_clouds" << iter << ".pcd";
		//io::savePCDFileASCII(ss.str(), *copy_cloud);
		int *rgb = rand_rgb();//随机生成0-255的颜色值
		visualization::PointCloudColorHandlerCustomrgb1(final_cloud, rgb[0], rgb[1], rgb[2]);//提取的平面不同彩色展示
		delete[]rgb;
		viewer->addPointCloud(final_cloud, rgb1, ss.str());
		viewer->setPointCloudRenderingProperties(visualization::PCL_VISUALIZER_POINT_SIZE, 3, ss.str());
	}
	viewer->spinOnce(1000);
	//将索引取反，获取剩余的点云数据，并展示******************************************************
	PointCloud::Ptr rest_cloud(new PointCloud);
	boost::shared_ptr>index_final = boost::make_shared>(index);
	ext.setInputCloud(sor_cloud);
	ext.setIndices(index_final);
	ext.setNegative(true);
	ext.filter(*rest_cloud);
	visualization::PCLVisualizer::Ptr viewer1(new visualization::PCLVisualizer("rest_clouds"));
	viewer1->addPointCloud(rest_cloud,"rest_clous");
	viewer1->setPointCloudRenderingProperties(visualization::PCL_VISUALIZER_POINT_SIZE, 3, "rest_clous");
	//io::savePCDFileASCII("C:\\Users\\Administrator\\Desktop\\rest_clouds", *rest_cloud);
	viewer1->spin();

	return 0;
}

结果：