[点云分割] 基于颜色的区域增长分割

效果：

代码：

#include <iostream>
#include <thread>
#include <vector>

#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
#include <pcl/search/search.h>
#include <pcl/search/kdtree.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/filters/filter_indices.h> // for pcl::removeNaNFromPointCloud
#include <pcl/segmentation/region_growing_rgb.h>

using namespace  std::chrono_literals;

int main()
{
    pcl::search::Search<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);

    pcl::PointCloud<pcl::PointXYZRGB>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGB>);
    if( pcl::io::loadPCDFile<pcl::PointXYZRGB>("region_growing_rgb_tutorial.pcd", *cloud) == -1)
    {
        std::cout << "cloud reading failed." << std::endl;
        return (-1);
    }

    pcl::IndicesPtr indices (new std::vector<int>);
    pcl::removeNaNFromPointCloud(*cloud, *indices); //从点云中移除包含NaN值的点，并返回非NaN点的索引

    pcl::RegionGrowingRGB<pcl::PointXYZRGB> reg;
    reg.setInputCloud(cloud);
    reg.setIndices(indices);
    reg.setSearchMethod(tree);
    reg.setDistanceThreshold(10);
    reg.setPointColorThreshold(6);
    reg.setRegionColorThreshold(5);
    reg.setMinClusterSize(600);

    std::vector<pcl::PointIndices> clusters;
    reg.extract(clusters);


    pcl::PointCloud <pcl::PointXYZRGB>::Ptr colored_cloud = reg.getColoredCloud();
    pcl::visualization::CloudViewer viewer("cluster viewer");
    viewer.showCloud(colored_cloud);
    while (!viewer.wasStopped()) {
        std::this_thread::sleep_for(100);
    }

    return(0);

}