HALCON 20.11.0.0 / HALCON Operator Reference / Segmentation / Classification
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class_2dim_supclass_2dim_supClass2dimSupClass2dimSupclass_2dim_sup (Operator)

Name

class_2dim_supclass_2dim_supClass2dimSupClass2dimSupclass_2dim_sup — Segment an image using two-dimensional pixel classification.

Signature

class_2dim_sup(ImageCol, ImageRow, FeatureSpace : RegionClass2Dim : : )

Herror class_2dim_sup(const Hobject ImageCol, const Hobject ImageRow, const Hobject FeatureSpace, Hobject* RegionClass2Dim)

Herror T_class_2dim_sup(const Hobject ImageCol, const Hobject ImageRow, const Hobject FeatureSpace, Hobject* RegionClass2Dim)

void Class2dimSup(const HObject& ImageCol, const HObject& ImageRow, const HObject& FeatureSpace, HObject* RegionClass2Dim)

HRegion HImage::Class2dimSup(const HImage& ImageRow, const HRegion& FeatureSpace) const

static void HOperatorSet.Class2dimSup(HObject imageCol, HObject imageRow, HObject featureSpace, out HObject regionClass2Dim)

HRegion HImage.Class2dimSup(HImage imageRow, HRegion featureSpace)

def class_2dim_sup(image_col: HObject, image_row: HObject, feature_space: HObject) -> HObject

Description

class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup classifies the points in two-channel images using a two-dimensional feature space. For each point, two gray values (one from each image) are used as features. The feature space is represented by the input region. The classification is done as follows:

A point from the input region of an image is accepted if the point (g_{r},g_{c}), which is determined by the respective gray values, is contained in the region FeatureSpaceFeatureSpaceFeatureSpaceFeatureSpacefeatureSpacefeature_space. g_{r} is here a gray value from the image ImageRowImageRowImageRowImageRowimageRowimage_row, while g_{c} is the corresponding gray value from ImageColImageColImageColImageColimageColimage_col.

Let P be a point with the coordinates P=(R,C), g_{r} be the gray value at position (R,C) in the image ImageRowImageRowImageRowImageRowimageRowimage_row, and g_{c} be the gray value at position (R,C) in the image ImageColImageColImageColImageColimageColimage_col. Then the point P is aggregated into the output region if g_{r} is interpreted as row coordinate and g_{c} as column coordinate.

For the generation of FeatureSpaceFeatureSpaceFeatureSpaceFeatureSpacefeatureSpacefeature_space, see histo_2dimhisto_2dimHisto2dimHisto2dimHisto2dimhisto_2dim. The feature space can be modified by applying region transformation operators, such as rank_regionrank_regionRankRegionRankRegionRankRegionrank_region, dilation1dilation1Dilation1Dilation1Dilation1dilation1, shape_transshape_transShapeTransShapeTransShapeTransshape_trans, elliptic_axiselliptic_axisEllipticAxisEllipticAxisEllipticAxiselliptic_axis, etc., before calling class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup.

The parameters ImageColImageColImageColImageColimageColimage_col and ImageRowImageRowImageRowImageRowimageRowimage_row must contain an equal number of images with the same size. The image points are taken from the intersection of the domains of both images (see reduce_domainreduce_domainReduceDomainReduceDomainReduceDomainreduce_domain).

Execution Information

Parameters

ImageColImageColImageColImageColimageColimage_col (input_object)  singlechannelimage(-array) → objectHImageHObjectHImageHobject (byte / direction / cyclic / int1)

Input image (first channel).

ImageRowImageRowImageRowImageRowimageRowimage_row (input_object)  singlechannelimage(-array) → objectHImageHObjectHImageHobject (byte / direction / cyclic / int1)

Input image (second channel).

FeatureSpaceFeatureSpaceFeatureSpaceFeatureSpacefeatureSpacefeature_space (input_object)  region(-array) → objectHRegionHObjectHRegionHobject

Region defining the feature space.

RegionClass2DimRegionClass2DimRegionClass2DimRegionClass2DimregionClass2Dimregion_class_2dim (output_object)  region(-array) → objectHRegionHObjectHRegionHobject *

Classified regions.

Example (C++ (HALCON 5.0-10.0))

#include "HIOStream.h"
#if !defined(USE_IOSTREAM_H)
using namespace std;
#endif
#include "HalconCpp.h"
using namespace Halcon;

int main (int argc, char *argv[])
{
  if (argc != 2)
  {
    cout << "Usage : " << argv[0] << " 'image' " << endl;
    return (-1);
  }

  HRegion   feats, cd2reg;
  HImage    image (argv[1]),
            text1, text2,
            mean1, mean2,
            histo;

  HWindow   win;
  Hlong      nc;

  if ((nc = image.CountChannels ()) != 3)
  {
    cout << argv[1] << " is not a rgb-image " << endl;
    return (-2);
  }

  image.Display (win);

  win.SetColor ("green");
  cout << "Draw the region of interrest " << endl;

  HRegion  region = win.DrawRegion ();

  text1 = image.TextureLaws ("el", 2, 5);
  mean1 = text1.MeanImage (21, 21);
  text2 = mean1.TextureLaws ("es", 2, 5);
  mean2 = text2.MeanImage (21, 21);

  histo = region.Histo2dim (mean1, mean2);
  feats = histo.Threshold (1.0, 1000000.0);

  win.SetDraw ("fill");
  win.SetColor ("red");

  feats.Display (win);

  cout << "Charakteristics area in red" << endl;

  cd2reg = mean1.Class2dimSup (mean2, feats);

  win.SetColor ("blue");
  cd2reg.Display (win);

  cout << "Result of classification in blue " << endl;
  win.Click ();
  return (0);
}

Example (C)

read_image(&Image,"combine");
open_window(0,0,-1,-1,0,"visible","",&WindowHandle);
disp_image(Image,WindowHandle);
fwrite_string("draw region of interest with the mouse");
fnew_line();
set_color(WindowHandle,"green");
draw_region(&Testreg,draw_region);
/* Texture transformation for 2-dimensional charachteristic */
texture_laws(Image,&T1,"el",2,5);
mean_image(T1,&M1,21,21);
texture_laws(M1,&T2,"es,",2,5);
mean_image(T2,&M2,21,21);
/* 2-dimensinal histogram of the test region */
histo_2dim(Testreg,M1,M2,&Histo);
/* All points occuring at least once */
threshold(Histo,&FeatureSpace,1.0,100000.0);
set_draw(WindowHandle,"fill");
set_color(WindowHandle,"red");
disp_region(FeatureSpace,WindowHandle);
fwrite_string("Characteristics area in red");
fnew_line();
/* Segmentation */
class_2dim_sup(M1,M2,FeatureSpace,&RegionClass2Dim);
set_color(WindowHandle,"blue");
disp_region(RegionClass2Dim,WindowHandle);
fwrite_string("Result of classification in blue");
fnew_line();

Example (C++ (HALCON 5.0-10.0))

#include "HIOStream.h"
#if !defined(USE_IOSTREAM_H)
using namespace std;
#endif
#include "HalconCpp.h"
using namespace Halcon;

int main (int argc, char *argv[])
{
  if (argc != 2)
  {
    cout << "Usage : " << argv[0] << " 'image' " << endl;
    return (-1);
  }

  HRegion   feats, cd2reg;
  HImage    image (argv[1]),
            text1, text2,
            mean1, mean2,
            histo;

  HWindow   win;
  Hlong      nc;

  if ((nc = image.CountChannels ()) != 3)
  {
    cout << argv[1] << " is not a rgb-image " << endl;
    return (-2);
  }

  image.Display (win);

  win.SetColor ("green");
  cout << "Draw the region of interrest " << endl;

  HRegion  region = win.DrawRegion ();

  text1 = image.TextureLaws ("el", 2, 5);
  mean1 = text1.MeanImage (21, 21);
  text2 = mean1.TextureLaws ("es", 2, 5);
  mean2 = text2.MeanImage (21, 21);

  histo = region.Histo2dim (mean1, mean2);
  feats = histo.Threshold (1.0, 1000000.0);

  win.SetDraw ("fill");
  win.SetColor ("red");

  feats.Display (win);

  cout << "Charakteristics area in red" << endl;

  cd2reg = mean1.Class2dimSup (mean2, feats);

  win.SetColor ("blue");
  cd2reg.Display (win);

  cout << "Result of classification in blue " << endl;
  win.Click ();
  return (0);
}

Example (C++ (HALCON 5.0-10.0))

#include "HIOStream.h"
#if !defined(USE_IOSTREAM_H)
using namespace std;
#endif
#include "HalconCpp.h"
using namespace Halcon;

int main (int argc, char *argv[])
{
  if (argc != 2)
  {
    cout << "Usage : " << argv[0] << " 'image' " << endl;
    return (-1);
  }

  HRegion   feats, cd2reg;
  HImage    image (argv[1]),
            text1, text2,
            mean1, mean2,
            histo;

  HWindow   win;
  Hlong      nc;

  if ((nc = image.CountChannels ()) != 3)
  {
    cout << argv[1] << " is not a rgb-image " << endl;
    return (-2);
  }

  image.Display (win);

  win.SetColor ("green");
  cout << "Draw the region of interrest " << endl;

  HRegion  region = win.DrawRegion ();

  text1 = image.TextureLaws ("el", 2, 5);
  mean1 = text1.MeanImage (21, 21);
  text2 = mean1.TextureLaws ("es", 2, 5);
  mean2 = text2.MeanImage (21, 21);

  histo = region.Histo2dim (mean1, mean2);
  feats = histo.Threshold (1.0, 1000000.0);

  win.SetDraw ("fill");
  win.SetColor ("red");

  feats.Display (win);

  cout << "Charakteristics area in red" << endl;

  cd2reg = mean1.Class2dimSup (mean2, feats);

  win.SetColor ("blue");
  cd2reg.Display (win);

  cout << "Result of classification in blue " << endl;
  win.Click ();
  return (0);
}

Example (C++ (HALCON 5.0-10.0))

#include "HIOStream.h"
#if !defined(USE_IOSTREAM_H)
using namespace std;
#endif
#include "HalconCpp.h"
using namespace Halcon;

int main (int argc, char *argv[])
{
  if (argc != 2)
  {
    cout << "Usage : " << argv[0] << " 'image' " << endl;
    return (-1);
  }

  HRegion   feats, cd2reg;
  HImage    image (argv[1]),
            text1, text2,
            mean1, mean2,
            histo;

  HWindow   win;
  Hlong      nc;

  if ((nc = image.CountChannels ()) != 3)
  {
    cout << argv[1] << " is not a rgb-image " << endl;
    return (-2);
  }

  image.Display (win);

  win.SetColor ("green");
  cout << "Draw the region of interrest " << endl;

  HRegion  region = win.DrawRegion ();

  text1 = image.TextureLaws ("el", 2, 5);
  mean1 = text1.MeanImage (21, 21);
  text2 = mean1.TextureLaws ("es", 2, 5);
  mean2 = text2.MeanImage (21, 21);

  histo = region.Histo2dim (mean1, mean2);
  feats = histo.Threshold (1.0, 1000000.0);

  win.SetDraw ("fill");
  win.SetColor ("red");

  feats.Display (win);

  cout << "Charakteristics area in red" << endl;

  cd2reg = mean1.Class2dimSup (mean2, feats);

  win.SetColor ("blue");
  cd2reg.Display (win);

  cout << "Result of classification in blue " << endl;
  win.Click ();
  return (0);
}

Complexity

Let A be the area of the input region. Then the runtime complexity is O(256^2 + A).

Result

class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup returns 2 (H_MSG_TRUE). If all parameters are correct, the behavior with respect to the input images and output regions can be determined by setting the values of the flags 'no_object_result'"no_object_result""no_object_result""no_object_result""no_object_result""no_object_result", 'empty_region_result'"empty_region_result""empty_region_result""empty_region_result""empty_region_result""empty_region_result", and 'store_empty_region'"store_empty_region""store_empty_region""store_empty_region""store_empty_region""store_empty_region" with set_systemset_systemSetSystemSetSystemSetSystemset_system. If necessary, an exception is raised.

Possible Predecessors

histo_2dimhisto_2dimHisto2dimHisto2dimHisto2dimhisto_2dim, thresholdthresholdThresholdThresholdThresholdthreshold, draw_regiondraw_regionDrawRegionDrawRegionDrawRegiondraw_region, dilation1dilation1Dilation1Dilation1Dilation1dilation1, openingopeningOpeningOpeningOpeningopening, shape_transshape_transShapeTransShapeTransShapeTransshape_trans

Possible Successors

connectionconnectionConnectionConnectionConnectionconnection, select_shapeselect_shapeSelectShapeSelectShapeSelectShapeselect_shape, select_grayselect_graySelectGraySelectGraySelectGrayselect_gray

Alternatives

class_ndim_normclass_ndim_normClassNdimNormClassNdimNormClassNdimNormclass_ndim_norm, thresholdthresholdThresholdThresholdThresholdthreshold

See also

histo_2dimhisto_2dimHisto2dimHisto2dimHisto2dimhisto_2dim

Module

Foundation

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