min_max_graymin_max_grayMinMaxGraymin_max_grayMinMaxGrayMinMaxGray (Operator)

Name

min_max_graymin_max_grayMinMaxGraymin_max_grayMinMaxGrayMinMaxGray — Determine the minimum and maximum gray values within regions.

Signature

min_max_gray(Regions, Image : : Percent : Min, Max, Range)

The operator min_max_graymin_max_grayMinMaxGraymin_max_grayMinMaxGrayMinMaxGray creates the histogram of the absolute frequencies of the gray values within RegionsRegionsRegionsRegionsRegionsregions in the input image ImageImageImageImageImageimage (see gray_histogray_histoGrayHistogray_histoGrayHistoGrayHisto) and calculates the number of pixels PercentPercentPercentPercentPercentpercent corresponding to the area of the input image. Then it goes inwards on both sides of the histogram by this number of pixels and determines the smallest and the largest gray value:

  e.g.:
    Area = 60, percent = 5, i.e. 3 pixels
    Histogram = [2,8,0,7,13,0,0,...,0,10,10,5,3,1,1]
    => Maximum = 255, Minimum = 0, Range = 255

    min_max_gray returns: Maximum = 253, Minimum = 1, Range = 252

For images of type int4, int8, and real, the above calculation is not performed via histograms, but using a rank selection algorithm. If PercentPercentPercentPercentPercentpercent is set to 50, MinMinMinMinMinmin = MaxMaxMaxMaxMaxmax = Median. If PercentPercentPercentPercentPercentpercent is 0 no histogram is calculated in order to enhance the runtime.

Attention

Note that the operator min_max_graymin_max_grayMinMaxGraymin_max_grayMinMaxGrayMinMaxGray only considers the given RegionsRegionsRegionsRegionsRegionsregions and ignores any previously set domain of the input image ImageImageImageImageImageimage.

Parallelization

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Automatically parallelized on tuple level.

Parameters

RegionsRegionsRegionsRegionsRegionsregions (input_object) region(-array) → object

Regions, the features of which are to be calculated.

ImageImageImageImageImageimage (input_object) singlechannelimage → object (byte / direction / cyclic / int1 / int2 / uint2 / int4 / int8 / real)

Gray value image.

PercentPercentPercentPercentPercentpercent (input_control) number → (real / integer)

Percentage below (above) the absolute maximum (minimum).

Default value: 0

Suggested values: 0, 1, 2, 5, 7, 10, 15, 20, 30, 40, 50

Restriction: 0 <= Percent && Percent <= 50

MinMinMinMinMinmin (output_control) real(-array) → (real)

“Minimum” gray value.

MaxMaxMaxMaxMaxmax (output_control) real(-array) → (real)

“Maximum” gray value.

Assertion: Max >= Min

RangeRangeRangeRangeRangerange (output_control) real(-array) → (real)

Difference between Max and Min.

Assertion: Range >= 0

Example (HDevelop)

* Threshold segmentation with training region:
read_image(Image,'fabrik')
draw_region(Region,WindowHandle)
min_max_gray(Region,Image,5,Min,Max,_)
threshold(Image,Seg,Min,Max)
disp_region(Seg,WindowHandle)

Example (C)

/* Threshold segmentation with training region: */
read_image(&Image,"fabrik");
draw_region(&Region,WindowHandle);
min_max_gray(Region,Image,5.0,&Min,&Max,NULL);
threshold(Image,&Seg,Min,Max);
disp_region(Seg,WindowHandle);

Example (HDevelop)

* Threshold segmentation with training region:
read_image(Image,'fabrik')
draw_region(Region,WindowHandle)
min_max_gray(Region,Image,5,Min,Max,_)
threshold(Image,Seg,Min,Max)
disp_region(Seg,WindowHandle)

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

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

main()
{
  HImage   img ("fabrik");
  HWindow  w;

  Htuple   range, max;

  img.Display (w);
  w.Click ();

  HRegion   reg = w.DrawRegion ();
  HImage    rdd = img.ReduceDomain (reg);

  Htuple min = reg.MinMaxGray (rdd, 5, &max, &range);

  HRegionArray imgseg = ((img >= min[0].I()).Connection() &
                         (img <= max[0].I()).Connection());

  cout << "Min = " << min[0].I() << endl;
  cout << "Max = " << max[0].I() << endl;

  imgseg.Display (w);
  w.Click ();
  return(0);
}

Example (HDevelop)

* Threshold segmentation with training region:
read_image(Image,'fabrik')
draw_region(Region,WindowHandle)
min_max_gray(Region,Image,5,Min,Max,_)
threshold(Image,Seg,Min,Max)
disp_region(Seg,WindowHandle)

Example (HDevelop)

* Threshold segmentation with training region:
read_image(Image,'fabrik')
draw_region(Region,WindowHandle)
min_max_gray(Region,Image,5,Min,Max,_)
threshold(Image,Seg,Min,Max)
disp_region(Seg,WindowHandle)