vigra - voronoi.cxx

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voronoi.cxx |

Generate a Voronoi diagram, using distanceTransform() and seededRegionGrowing()
Usage: `voronoi`, generates: `distances.gif` (Euclidean distance transform) and `voronoi.gif` (Voronoi diagram)

/************************************************************************/
/* */
/* Copyright 1998-2002 by Ullrich Koethe */
/* */
/* This file is part of the VIGRA computer vision library. */
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/* http://hci.iwr.uni-heidelberg.de/vigra/ */
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/* ullrich.koethe@iwr.uni-heidelberg.de or */
/* vigra@informatik.uni-hamburg.de */
/* */
/* Permission is hereby granted, free of charge, to any person */
/* obtaining a copy of this software and associated documentation */
/* files (the "Software"), to deal in the Software without */
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/************************************************************************/
#include <iostream>
#include <vigra/multi_array.hxx>
#include <vigra/random.hxx>
#include <vigra/distancetransform.hxx>
#include <vigra/labelimage.hxx>
#include <vigra/seededregiongrowing.hxx>
#include <vigra/impex.hxx>
using namespace vigra;
int main(int argc, char ** argv)
{
try
{
int number_of_points = 25;
int size = 512;
// create input image
MultiArray<2, float> in(size, size);
MersenneTwister random;
for(int i=1; i<=number_of_points; ++i)
{
// mark a number of points
int x = random. uniformInt(size);
int y = random.uniformInt(size);
// label each point with a unique number
in(x,y) = i;
}
// create output image and paint it white
MultiArray<2, int> out(size, size);
out = 255;
// in the output image, paint the points black which were
// marked in the input image
initImageIf(out, in, 0);
// create image to hold the distance transform
MultiArray<2, float> distances(size, size);
// calculate Euclidean distance transform
// all pixels with value 0 are considered background
distanceTransform(in, distances, 0, 2);
exportImage(distances, ImageExportInfo("distances.gif"));
std::cout << "Wrote distance transform (distances.gif)" << std::endl;
// initialize statistics functor for region growing
ArrayOfRegionStatistics<SeedRgDirectValueFunctor<float> > statistics(number_of_points);
// perform region growing, starting at the points marked in the input
// image; as the feature (first source) image contains the distances,
// the will calculate the voronoi regions of these points
seededRegionGrowing(distances, in, in, statistics);
// in the output image, mark the borders of the voronoi regions black
regionImageToEdgeImage(in, out, 0);
exportImage(out, ImageExportInfo("voronoi.gif"));
std::cout << "Wrote voronoi diagram (voronoi.gif)" << std::endl;
}
catch (std::exception & e)
{
std::cout << e.what() << std::endl;
return 1;
}
return 0;
}

© Ullrich Köthe (ullrich.koethe@iwr.uni-heidelberg.de) Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany | html generated using doxygen and Python vigra 1.10.0 (Mon Nov 18 2013)