region_growing_rgb.h

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 * Author : Sergey Ushakov
 * Email  : mine_all_mine@bk.ru
 *
 */
 
#pragma once
 
#include <pcl/memory.h>
#include <pcl/pcl_macros.h>
#include <pcl/segmentation/region_growing.h>
 
namespace pcl
{
  /** \brief
    * Implements the well known Region Growing algorithm used for segmentation based on color of points.
    * Description can be found in the article
    * "Color-based segmentation of point clouds"
    * by Qingming Zhan, Yubin Liang, Yinghui Xiao
    * \ingroup segmentation
    */
  template <typename PointT, typename NormalT = pcl::Normal>
  class PCL_EXPORTS RegionGrowingRGB : public RegionGrowing<PointT, NormalT>
  {
    public:
 
      using RegionGrowing<PointT, NormalT>::input_;
      using RegionGrowing<PointT, NormalT>::indices_;
      using RegionGrowing<PointT, NormalT>::initCompute;
      using RegionGrowing<PointT, NormalT>::deinitCompute;
      using RegionGrowing<PointT, NormalT>::normals_;
      using RegionGrowing<PointT, NormalT>::normal_flag_;
      using RegionGrowing<PointT, NormalT>::curvature_flag_;
      using RegionGrowing<PointT, NormalT>::residual_flag_;
      using RegionGrowing<PointT, NormalT>::residual_threshold_;
      using RegionGrowing<PointT, NormalT>::neighbour_number_;
      using RegionGrowing<PointT, NormalT>::search_;
      using RegionGrowing<PointT, NormalT>::min_pts_per_cluster_;
      using RegionGrowing<PointT, NormalT>::max_pts_per_cluster_;
      using RegionGrowing<PointT, NormalT>::smooth_mode_flag_;
      using RegionGrowing<PointT, NormalT>::theta_threshold_;
      using RegionGrowing<PointT, NormalT>::curvature_threshold_;
      using RegionGrowing<PointT, NormalT>::point_neighbours_;
      using RegionGrowing<PointT, NormalT>::point_labels_;
      using RegionGrowing<PointT, NormalT>::num_pts_in_segment_;
      using RegionGrowing<PointT, NormalT>::clusters_;
      using RegionGrowing<PointT, NormalT>::number_of_segments_;
      using RegionGrowing<PointT, NormalT>::applySmoothRegionGrowingAlgorithm;
      using RegionGrowing<PointT, NormalT>::assembleRegions;
 
    public:
 
      /** \brief Constructor that sets default values for member variables. */
      RegionGrowingRGB ();
 
      /** \brief Destructor that frees memory. */
      
      ~RegionGrowingRGB () override;
 
      /** \brief Returns the color threshold value used for testing if points belong to the same region. */
      float
      getPointColorThreshold () const;
 
      /** \brief This method specifies the threshold value for color test between the points.
        * This kind of testing is made at the first stage of the algorithm(region growing).
        * If the difference between points color is less than threshold value, then they are considered
        * to be in the same region.
        * \param[in] thresh new threshold value for color test
        */
      void
      setPointColorThreshold (float thresh);
 
      /** \brief Returns the color threshold value used for testing if regions can be merged. */
      float
      getRegionColorThreshold () const;
 
      /** \brief This method specifies the threshold value for color test between the regions.
        * This kind of testing is made at the second stage of the algorithm(region merging).
        * If the difference between segments color is less than threshold value, then they are merged together.
        * \param[in] thresh new threshold value for color test
        */
      void
      setRegionColorThreshold (float thresh);
 
      /** \brief Returns the distance threshold. If the distance between two points is less or equal to
        * distance threshold value, then those points assumed to be neighbouring points.
        */
      float
      getDistanceThreshold () const;
 
      /** \brief Allows to set distance threshold.
        * \param[in] thresh new threshold value for neighbour test
        */
      void
      setDistanceThreshold (float thresh);
 
      /** \brief Returns the number of nearest neighbours used for searching K nearest segments.
        * Note that here it refers to the segments(not the points).
        */
      unsigned int
      getNumberOfRegionNeighbours () const;
 
      /** \brief This method allows to set the number of neighbours that is used for finding
        * neighbouring segments. Neighbouring segments are needed for the merging process.
        * \param[in] nghbr_number the number of neighbouring segments to find
        */
      void
      setNumberOfRegionNeighbours (unsigned int nghbr_number);
 
      /** \brief Returns the flag that signalize if the smoothness test is turned on/off. */
      bool
      getNormalTestFlag () const;
 
       /** \brief
         * Allows to turn on/off the smoothness test.
         * \param[in] value new value for normal/smoothness test. If set to true then the test will be turned on
         */
      void
      setNormalTestFlag (bool value);
 
      /** \brief Allows to turn on/off the curvature test.
        * \param[in] value new value for curvature test. If set to true then the test will be turned on
        */
      void
      setCurvatureTestFlag (bool value) override;
 
      /** \brief
        * Allows to turn on/off the residual test.
        * \param[in] value new value for residual test. If set to true then the test will be turned on
        */
      void
      setResidualTestFlag (bool value) override;
 
      /** \brief This method launches the segmentation algorithm and returns the clusters that were
        * obtained during the segmentation.
        * \param[out] clusters clusters that were obtained. Each cluster is an array of point indices.
        */
      void
      extract (std::vector <pcl::PointIndices>& clusters) override;
 
      /** \brief For a given point this function builds a segment to which it belongs and returns this segment.
        * \param[in] index index of the initial point which will be the seed for growing a segment.
        * \param cluster
        */
      void
      getSegmentFromPoint (index_t index, pcl::PointIndices& cluster) override;
 
    protected:
 
      /** \brief This method simply checks if it is possible to execute the segmentation algorithm with
        * the current settings. If it is possible then it returns true.
        */
      bool
      prepareForSegmentation () override;
 
      /** \brief This method finds KNN for each point and saves them to the array
        * because the algorithm needs to find KNN a few times.
        */
      void
      findPointNeighbours () override;
 
      /** \brief This method simply calls the findRegionsKNN for each segment and
        * saves the results for later use.
        */
      void
      findSegmentNeighbours ();
 
      /** \brief This method finds K nearest neighbours of the given segment.
        * \param[in] index index of the segment for which neighbours will be found
        * \param[in] nghbr_number the number of neighbours to find
        * \param[out] nghbrs the array of indices of the neighbours that were found
        * \param[out] dist the array of distances to the corresponding neighbours
        */
      void
      findRegionsKNN (pcl::index_t index, pcl::uindex_t nghbr_number, Indices& nghbrs, std::vector<float>& dist);
 
      /** \brief This function implements the merging algorithm described in the article
        * "Color-based segmentation of point clouds"
        * by Qingming Zhan, Yubin Liang, Yinghui Xiao
        */
      void
      applyRegionMergingAlgorithm ();
 
      /** \brief This method calculates the colorimetrical difference between two points.
        * In this case it simply returns the euclidean distance between two colors.
        * \param[in] first_color the color of the first point
        * \param[in] second_color the color of the second point
        */
      float
      calculateColorimetricalDifference (std::vector<unsigned int>& first_color, std::vector<unsigned int>& second_color) const;
 
      /** \brief This method assembles the array containing neighbours of each homogeneous region.
        * Homogeneous region is the union of some segments. This array is used when the regions
        * with a few points need to be merged with the neighbouring region.
        * \param[out] neighbours_out vector of lists of neighbours for every homogeneous region
        * \param[in] regions_in vector of lists, each list contains indices of segments that belong
        * to the corresponding homogeneous region.
        */
      void
      findRegionNeighbours (std::vector< std::vector< std::pair<float, pcl::index_t> > >& neighbours_out, std::vector< std::vector<int> >& regions_in);
 
      /** \brief This function simply assembles the regions from list of point labels.
        * \param[in] num_pts_in_region for each final region it stores the corresponding number of points in it
        * \param[in] num_regions number of regions to assemble
        */
      void
      assembleRegions (std::vector<unsigned int>& num_pts_in_region, int num_regions);
 
      /** \brief This function is checking if the point with index 'nghbr' belongs to the segment.
        * If so, then it returns true. It also checks if this point can serve as the seed.
        * \param[in] initial_seed index of the initial point that was passed to the growRegion() function
        * \param[in] point index of the current seed point
        * \param[in] nghbr index of the point that is neighbour of the current seed
        * \param[out] is_a_seed this value is set to true if the point with index 'nghbr' can serve as the seed
        */
      bool
      validatePoint (index_t initial_seed, index_t point, index_t nghbr, bool& is_a_seed) const override;
 
    protected:
 
      /** \brief Thershold used in color test for points. */
      float color_p2p_threshold_{1225.0f};
 
      /** \brief Thershold used in color test for regions. */
      float color_r2r_threshold_{10.0f};
 
      /** \brief Threshold that tells which points we need to assume neighbouring. */
      float distance_threshold_{0.05f};
 
      /** \brief Number of neighbouring segments to find. */
      unsigned int region_neighbour_number_{100};
 
      /** \brief Stores distances for the point neighbours from point_neighbours_ */
      std::vector< std::vector<float> > point_distances_;
 
      /** \brief Stores the neighboures for the corresponding segments. */
      std::vector< pcl::Indices > segment_neighbours_;
 
      /** \brief Stores distances for the segment neighbours from segment_neighbours_ */
      std::vector< std::vector<float> > segment_distances_;
 
      /** \brief Stores new indices for segments that were obtained at the region growing stage. */
      std::vector<int> segment_labels_;
 
    public:
      PCL_MAKE_ALIGNED_OPERATOR_NEW
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/segmentation/impl/region_growing_rgb.hpp>
#endif