Operator Reference

HALCON Operator Reference / Segmentation / Threshold
ClassesClasses | | Operators

dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold (Operator)

dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold — Threshold operator for signed images.

Signature

dual_threshold(Image : RegionCrossings : MinSize, MinGray, Threshold : )

Herror dual_threshold(const Hobject Image, Hobject* RegionCrossings, const Hlong MinSize, double MinGray, double Threshold)

Herror T_dual_threshold(const Hobject Image, Hobject* RegionCrossings, const Htuple MinSize, const Htuple MinGray, const Htuple Threshold)

void DualThreshold(const HObject& Image, HObject* RegionCrossings, const HTuple& MinSize, const HTuple& MinGray, const HTuple& Threshold)

HRegion HImage::DualThreshold(Hlong MinSize, double MinGray, double Threshold) const

static void HOperatorSet.DualThreshold(HObject image, out HObject regionCrossings, HTuple minSize, HTuple minGray, HTuple threshold)

HRegion HImage.DualThreshold(int minSize, double minGray, double threshold)

def dual_threshold(image: HObject, min_size: int, min_gray: float, threshold: float) -> HObject

Description

dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold segments the input image into a region with gray values ThresholdThresholdThresholdthresholdthreshold (“positive” regions) and a region with gray values ThresholdThresholdThresholdthresholdthreshold (“negative” regions). Only “positive” or “negative” regions having a size larger than MinSizeMinSizeMinSizeminSizemin_size are taken into account. And regions whose maximum gray value is less than MinGrayMinGrayMinGrayminGraymin_gray in absolute value are suppressed.

The segmentation performed is not complete, i.e., the “positive” and “negative” regions together do not necessarily cover the entire image: Areas with a gray value between ThresholdThresholdThresholdthresholdthreshold and ThresholdThresholdThresholdthresholdthreshold, MinGrayMinGrayMinGrayminGraymin_gray and MinGrayMinGrayMinGrayminGraymin_gray, respectively, are not taken into account.

dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold is usually called after applying a Laplace operator (laplacelaplaceLaplaceLaplacelaplace, laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss, derivate_gaussderivate_gaussDerivateGaussDerivateGaussderivate_gauss or diff_of_gaussdiff_of_gaussDiffOfGaussDiffOfGaussdiff_of_gauss) to an image or with the difference of two images (sub_imagesub_imageSubImageSubImagesub_image).

The zero crossings of a Laplace image correspond to edges in an image, and are the separating regions of the “positive” and “negative” regions in the Laplace image. They can be determined by calling dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold with ThresholdThresholdThresholdthresholdthreshold = 1 and then creating the complement regions with complementcomplementComplementComplementcomplement. The parameter MinGrayMinGrayMinGrayminGraymin_gray determines the noise invariance, while MinSizeMinSizeMinSizeminSizemin_size determines the resolution of the edge detection.

Using byte images, only the positive part of the operator is applied. Therefore dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold behaves like a standard threshold operator (thresholdthresholdThresholdThresholdthreshold) with successive connectionconnectionConnectionConnectionconnection and select_grayselect_graySelectGraySelectGrayselect_gray.

Execution Information

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

Parameters

ImageImageImageimageimage (input_object)  singlechannelimage(-array) → objectHImageHObjectHObjectHobject (byte / int1 / int2 / int4 / real)

Input image.

RegionCrossingsRegionCrossingsRegionCrossingsregionCrossingsregion_crossings (output_object)  region-array → objectHRegionHObjectHObjectHobject *

Positive and negative regions.

MinSizeMinSizeMinSizeminSizemin_size (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Regions smaller than MinSize are suppressed.

Default: 20

Suggested values: 0, 10, 20, 50, 100, 200, 500, 1000

Value range: 0 ≤ MinSize MinSize MinSize minSize min_size ≤ 10000 (lin)

Minimum increment: 1

Recommended increment: 10

MinGrayMinGrayMinGrayminGraymin_gray (input_control)  real → HTuplefloatHTupleHtuple (real) (double) (double) (double)

Regions whose maximum absolute gray value is smaller than MinGray are suppressed.

Default: 5.0

Suggested values: 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 9.0, 11.0, 15.0, 20.0

Value range: 0 ≤ MinGray MinGray MinGray minGray min_gray (lin)

Minimum increment: 1.0

Recommended increment: 10.0

ThresholdThresholdThresholdthresholdthreshold (input_control)  real → HTuplefloatHTupleHtuple (real) (double) (double) (double)

Regions that have a gray value smaller than Threshold (or larger than -Threshold) are suppressed.

Default: 2.0

Suggested values: 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 9.0, 11.0, 15.0, 20.0

Value range: 0 ≤ Threshold Threshold Threshold threshold threshold (lin)

Minimum increment: 1.0

Recommended increment: 10.0

Example (HDevelop)

* Edge detection with the Laplace operator (and edge thinning)
diff_of_gauss(Image,Laplace,2.0,1.6)
* find "`positive"' and "`negative"' regions:
dual_threshold(Laplace,Region,20,2,1)
* The zero runnings are the complement to these image section:
complement(Region,ZeroCrossings)

* Simulation of dual_threshold
dual_threshold(Laplace,Result,MinS,MinG,Threshold)
threshold(Laplace,Tmp1,Threshold,999999)
connection(Tmp1,Tmp2)
select_shape(Tmp2,Tmp3,'area','and',MinS,999999)
select_gray(Laplace,Tmp3,Tmp4,'max','and',MinG,999999)
threshold(Laplace,Tmp5,-999999,-Threshold)
connection(Tmp5,Tmp6)
select_shape(Tmp6,Tmp7,'area','and',MinS,999999)
select_gray(Laplace,Tmp7,Tmp8,'min','and',-999999,-MinG)
concat_obj(Tmp4,Tmp8,Result)

Example (C)

/* Edge detection with the Laplace operator (and edge thinning) */
diff_of_gauss(Image,&Laplace,2.0,1.6);
/* find "`positive"' and "`negative"' regions: */
dual_threshold(Laplace,&Region,20,2,1);
/*The zero runnings are the complement to these image section: */
complement(Region,ZeroCrossings);

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       image (argv[1]),
               laplace;
  HWindow      win;

  HRegionArray region,
               nulldg;

  image.Display (win);

  laplace = image.DiffOfGauss (2.0, 1.6);
  region  = laplace.DualThreshold (20, 2, 1);
  nulldg  = region.Complement ();

  laplace.Display (win);     win.Click ();
  region.Display (win);      win.Click ();
  nulldg.Display (win);      win.Click ();

  return (0);
}

Example (HDevelop)

* Edge detection with the Laplace operator (and edge thinning)
diff_of_gauss(Image,Laplace,2.0,1.6)
* find "`positive"' and "`negative"' regions:
dual_threshold(Laplace,Region,20,2,1)
* The zero runnings are the complement to these image section:
complement(Region,ZeroCrossings)

* Simulation of dual_threshold
dual_threshold(Laplace,Result,MinS,MinG,Threshold)
threshold(Laplace,Tmp1,Threshold,999999)
connection(Tmp1,Tmp2)
select_shape(Tmp2,Tmp3,'area','and',MinS,999999)
select_gray(Laplace,Tmp3,Tmp4,'max','and',MinG,999999)
threshold(Laplace,Tmp5,-999999,-Threshold)
connection(Tmp5,Tmp6)
select_shape(Tmp6,Tmp7,'area','and',MinS,999999)
select_gray(Laplace,Tmp7,Tmp8,'min','and',-999999,-MinG)
concat_obj(Tmp4,Tmp8,Result)

Result

dual_thresholddual_thresholdDualThresholdDualThresholddual_threshold 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

min_max_graymin_max_grayMinMaxGrayMinMaxGraymin_max_gray, sobel_ampsobel_ampSobelAmpSobelAmpsobel_amp, binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter, reduce_domainreduce_domainReduceDomainReduceDomainreduce_domain, diff_of_gaussdiff_of_gaussDiffOfGaussDiffOfGaussdiff_of_gauss, sub_imagesub_imageSubImageSubImagesub_image, derivate_gaussderivate_gaussDerivateGaussDerivateGaussderivate_gauss, laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss, laplacelaplaceLaplaceLaplacelaplace, expand_regionexpand_regionExpandRegionExpandRegionexpand_region

Possible Successors

connectionconnectionConnectionConnectionconnection, dilation1dilation1Dilation1Dilation1dilation1, erosion1erosion1Erosion1Erosion1erosion1, openingopeningOpeningOpeningopening, closingclosingClosingClosingclosing, rank_regionrank_regionRankRegionRankRegionrank_region, shape_transshape_transShapeTransShapeTransshape_trans, skeletonskeletonSkeletonSkeletonskeleton

Alternatives

thresholdthresholdThresholdThresholdthreshold, dyn_thresholddyn_thresholdDynThresholdDynThresholddyn_threshold, check_differencecheck_differenceCheckDifferenceCheckDifferencecheck_difference

See also

connectionconnectionConnectionConnectionconnection, select_shapeselect_shapeSelectShapeSelectShapeselect_shape, select_grayselect_graySelectGraySelectGrayselect_gray

Module

Foundation

ClassesClasses | | Operators