regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing (Operator)

Name

regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing — Segment an image using regiongrowing.

Signature

Description

regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing segments images into regions of the same intensity - rastered into rectangles of size RasterHeightRasterHeightRasterHeightrasterHeightraster_height RasterWidthRasterWidthRasterWidthrasterWidthraster_width. In order to decide whether two adjacent rectangles belong to the same region only the gray value of their center points is used. If the gray value difference is less then or equal to ToleranceToleranceTolerancetolerancetolerance the rectangles are merged into one region.

If and are two gray values to be examined, they are merged into the same region if: For images of type 'cyclic', the following formulas are used:

For rectangles larger than one pixel, usually the images should be smoothed with a lowpass filter with a size of at least RasterHeightRasterHeightRasterHeightrasterHeightraster_height RasterWidthRasterWidthRasterWidthrasterWidthraster_width before calling regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing (so that the gray values at the centers of the rectangles are “representative” for the whole rectangle). If the image contains little noise and the rectangles are small, the smoothing can be omitted in many cases.

The resulting regions are collections of rectangles of the chosen size RasterHeightRasterHeightRasterHeightrasterHeightraster_height RasterWidthRasterWidthRasterWidthrasterWidthraster_width. Only regions containing at least MinSizeMinSizeMinSizeminSizemin_size points are returned.

Regiongrowing is a very fast operation, and thus suited for time-critical applications.

Attention

RasterWidthRasterWidthRasterWidthrasterWidthraster_width and RasterHeightRasterHeightRasterHeightrasterHeightraster_height are automatically converted to odd values if necessary.

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.

Parameters

read_image(Image,'fabrik')
mean_image(Image,Mean,RasterHeight,RasterWidth)
regiongrowing(Mean,Result,RasterHeight,RasterWidth,6.0,100)

read_image(&Image,"fabrik");
mean_image(Image,&Mean,RasterHeight,RasterWidth);
regiongrowing(Mean,&Result,RasterHeight,RasterWidth,6,100);

#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] << " <name of the image>" << endl;
    return (-1);
  }

  HImage   image (argv[1]),
           mean;
  HWindow  win;

  mean = image.MeanImage (5, 5);

  HRegionArray reg = mean.Regiongrowing (5, 5, 6, 100);

  reg.Display (win);
  win.Click ();

  return (0);
}

read_image(Image,'fabrik')
mean_image(Image,Mean,RasterHeight,RasterWidth)
regiongrowing(Mean,Result,RasterHeight,RasterWidth,6.0,100)

Complexity

Let N be the number of found regions and M the number of points in one of these regions. Then the runtime complexity is O(N * log(M) * M).

Result

regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing 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

binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, mean_imagemean_imageMeanImageMeanImagemean_image, gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter, smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image, median_imagemedian_imageMedianImageMedianImagemedian_image, anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion

Possible Successors

select_shapeselect_shapeSelectShapeSelectShapeselect_shape, reduce_domainreduce_domainReduceDomainReduceDomainreduce_domain, select_grayselect_graySelectGraySelectGrayselect_gray

Alternatives

regiongrowing_nregiongrowing_nRegiongrowingNRegiongrowingNregiongrowing_n, regiongrowing_meanregiongrowing_meanRegiongrowingMeanRegiongrowingMeanregiongrowing_mean, label_to_regionlabel_to_regionLabelToRegionLabelToRegionlabel_to_region

Module

Foundation