class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup (Operator)
Name
class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup
— Segment two images by clustering.
Signature
Description
class_2dim_unsupclass_2dim_unsupClass2dimUnsupClass2dimUnsupclass_2dim_unsup
performs a classification with two
single-channel images. First, a two-dimensional histogram of the two
images is computed (histo_2dimhisto_2dimHisto2dimHisto2dimhisto_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_domainReduceDomainReduceDomainreduce_domain
). After this,
all pixels in the images that are at most ThresholdThresholdThresholdthresholdthreshold
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 NumClassesNumClassesNumClassesnumClassesnum_classes
times; thus,
NumClassesNumClassesNumClassesnumClassesnum_classes
output regions result. Only pixels defined in
both images are returned.
Attention
Both input images must have the same size.
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
Image1Image1Image1image1image_1
(input_object) singlechannelimage →
objectHImageHObjectHObjectHobject (byte)
First input image.
Image2Image2Image2image2image_2
(input_object) singlechannelimage →
objectHImageHObjectHObjectHobject (byte)
Second input image.
ClassesClassesClassesclassesclasses
(output_object) region-array →
objectHRegionHObjectHObjectHobject *
Classification result.
ThresholdThresholdThresholdthresholdthreshold
(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
NumClassesNumClassesNumClassesnumClassesnum_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++)
#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++)
#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++)
#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_unsupClass2dimUnsupClass2dimUnsupclass_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", '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" with set_systemset_systemSetSystemSetSystemset_system
.
If necessary, an exception is raised.
Possible Predecessors
decompose2decompose2Decompose2Decompose2decompose2
,
decompose3decompose3Decompose3Decompose3decompose3
,
median_imagemedian_imageMedianImageMedianImagemedian_image
,
anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion
,
reduce_domainreduce_domainReduceDomainReduceDomainreduce_domain
Possible Successors
select_shapeselect_shapeSelectShapeSelectShapeselect_shape
,
select_grayselect_graySelectGraySelectGrayselect_gray
,
connectionconnectionConnectionConnectionconnection
Alternatives
thresholdthresholdThresholdThresholdthreshold
,
histo_2dimhisto_2dimHisto2dimHisto2dimhisto_2dim
,
class_2dim_supclass_2dim_supClass2dimSupClass2dimSupclass_2dim_sup
,
class_ndim_normclass_ndim_normClassNdimNormClassNdimNormclass_ndim_norm
Module
Foundation