class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup (Operator)

Name

class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup — Segment two images by clustering.

Signature

class_2dim_unsup(Image1, Image2 : Classes : Threshold, NumClasses : )

Herror class_2dim_unsup(const Hobject Image1, const Hobject Image2, Hobject* Classes, const Hlong Threshold, const Hlong NumClasses)

Herror T_class_2dim_unsup(const Hobject Image1, const Hobject Image2, Hobject* Classes, const Htuple Threshold, const Htuple NumClasses)

void Class2dimUnsup(const HObject& Image1, const HObject& Image2, HObject* Classes, const HTuple& Threshold, const HTuple& NumClasses)

HRegion HImage::Class2dimUnsup(const HImage& Image2, Hlong Threshold, Hlong NumClasses) const

static void HOperatorSet.Class2dimUnsup(HObject image1, HObject image2, out HObject classes, HTuple threshold, HTuple numClasses)

HRegion HImage.Class2dimUnsup(HImage image2, int threshold, int numClasses)

def class_2dim_unsup(image_1: HObject, image_2: HObject, threshold: int, num_classes: int) -> HObject

Description

class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup performs a classification with two single-channel images. First, a two-dimensional histogram of the two images is computed (histo_2dimhisto_2dimHisto2dimHisto2dimHisto2dimhisto_2dim). In this histogram, the first maximum is extracted; it serves as the first cluster center. The histogram is computed with the intersection of the domains of both images (see reduce_domainreduce_domainReduceDomainReduceDomainReduceDomainreduce_domain). After this, all pixels in the images that are at most ThresholdThresholdThresholdThresholdthresholdthreshold pixels from the cluster center in the maximum norm, are determined. These pixels form one output region. Next, the pixels thus classified are deleted from the histogram so that they are not taken into account for the next class. In this modified histogram, again the maximum is extracted; it again serves as a cluster center. The above steps are repeated NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes times; thus, NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes output regions result. Only pixels defined in both images are returned.

Attention

Both input images must have the same size.

Execution Information

Parameters

Image1Image1Image1Image1image1image_1 (input_object)  singlechannelimage objectHImageHObjectHImageHobject (byte)

First input image.

Image2Image2Image2Image2image2image_2 (input_object)  singlechannelimage objectHImageHObjectHImageHobject (byte)

Second input image.

ClassesClassesClassesClassesclassesclasses (output_object)  region-array objectHRegionHObjectHRegionHobject *

Classification result.

ThresholdThresholdThresholdThresholdthresholdthreshold (input_control)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Threshold (maximum distance to the cluster's center).

Default: 15

Suggested values: 0, 2, 5, 8, 12, 17, 20, 30, 50, 70

NumClassesNumClassesNumClassesNumClassesnumClassesnum_classes (input_control)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Number of classes (cluster centers).

Default: 5

Suggested values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 30, 40, 50

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);
  }

  HImage   colimg (argv[1]),
           green, blue;

  HWindow  w;
  Hlong     nc;

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

  colimg.Display (w);

  HImage        red = colimg.Decompose3 (&green, &blue);
  HRegionArray  seg = red.Class2dimUnsup (green, 15, 5);

  w.SetDraw ("margin");
  w.SetColored (12);
  seg.Display (w);
  w.Click ();

  return (0);
}

Example (C)

read_image(&ColorImage,"patras");
decompose3(ColorImage,&Red,&Green,&Blue);
class_2dim_unsup(Red,Green,&Seg,15,5);
set_colored(WindowHandle,12);
disp_region(Seg,WindowHandle);

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);
  }

  HImage   colimg (argv[1]),
           green, blue;

  HWindow  w;
  Hlong     nc;

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

  colimg.Display (w);

  HImage        red = colimg.Decompose3 (&green, &blue);
  HRegionArray  seg = red.Class2dimUnsup (green, 15, 5);

  w.SetDraw ("margin");
  w.SetColored (12);
  seg.Display (w);
  w.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);
  }

  HImage   colimg (argv[1]),
           green, blue;

  HWindow  w;
  Hlong     nc;

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

  colimg.Display (w);

  HImage        red = colimg.Decompose3 (&green, &blue);
  HRegionArray  seg = red.Class2dimUnsup (green, 15, 5);

  w.SetDraw ("margin");
  w.SetColored (12);
  seg.Display (w);
  w.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);
  }

  HImage   colimg (argv[1]),
           green, blue;

  HWindow  w;
  Hlong     nc;

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

  colimg.Display (w);

  HImage        red = colimg.Decompose3 (&green, &blue);
  HRegionArray  seg = red.Class2dimUnsup (green, 15, 5);

  w.SetDraw ("margin");
  w.SetColored (12);
  seg.Display (w);
  w.Click ();

  return (0);
}

Result

class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup 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

decompose2decompose2Decompose2Decompose2Decompose2decompose2, decompose3decompose3Decompose3Decompose3Decompose3decompose3, median_imagemedian_imageMedianImageMedianImageMedianImagemedian_image, anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion, reduce_domainreduce_domainReduceDomainReduceDomainReduceDomainreduce_domain

Possible Successors

select_shapeselect_shapeSelectShapeSelectShapeSelectShapeselect_shape, select_grayselect_graySelectGraySelectGraySelectGrayselect_gray, connectionconnectionConnectionConnectionConnectionconnection

Alternatives

thresholdthresholdThresholdThresholdThresholdthreshold, histo_2dimhisto_2dimHisto2dimHisto2dimHisto2dimhisto_2dim, class_2dim_supclass_2dim_supClass2dimSupClass2dimSupClass2dimSupclass_2dim_sup, class_ndim_normclass_ndim_normClassNdimNormClassNdimNormClassNdimNormclass_ndim_norm

Module

Foundation