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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: itkHausdorffDistanceImageFilterTest.cxx
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include "itkDirectedHausdorffDistanceImageFilter.h"
#include "itkHausdorffDistanceImageFilter.h"
#include "itkImageRegionIterator.h"
#include "itkFilterWatcher.h"
int itkHausdorffDistanceImageFilterTest(int, char* [] )
{
typedef unsigned int Pixel1Type;
typedef float Pixel2Type;
enum { ImageDimension = 3 };
typedef itk::Image<Pixel1Type,ImageDimension> Image1Type;
typedef itk::Image<Pixel2Type,ImageDimension> Image2Type;
Image1Type::Pointer image1 = Image1Type::New();
Image2Type::Pointer image2 = Image2Type::New();
Image1Type::SizeType size;
size.Fill( 50 );
image1->SetRegions( size );
image2->SetRegions( size );
image1->Allocate();
image2->Allocate();
image1->FillBuffer( itk::NumericTraits<Pixel1Type>::Zero );
image2->FillBuffer( itk::NumericTraits<Pixel2Type>::Zero );
typedef Image1Type::RegionType RegionType;
RegionType region1;
RegionType region2;
typedef Image1Type::IndexType IndexType;
IndexType index;
size.Fill( 20 );
index.Fill( 10 );
region1.SetSize( size );
region1.SetIndex( index );
size.Fill( 15 );
index.Fill( 20 );
region2.SetSize( size );
region2.SetIndex( index );
itk::ImageRegionIterator<Image1Type> it1( image1, region1 );
Pixel1Type count = itk::NumericTraits<Pixel1Type>::Zero;
while ( !it1.IsAtEnd() )
{
it1.Set( ++count );
++it1;
}
itk::ImageRegionIterator<Image2Type> it2( image2, region2 );
while ( !it2.IsAtEnd() )
{
it2.Set( 7.2 );
++it2;
}
// compute the directed Hausdorff distance h(image1,image2)
{
typedef itk::DirectedHausdorffDistanceImageFilter<Image1Type,Image2Type> FilterType;
FilterType::Pointer filter = FilterType::New();
FilterWatcher watcher(filter, "filter");
filter->SetInput1( image1 );
filter->SetInput2( image2 );
filter->Update();
filter->Print( std::cout );
// check results
FilterType::RealType trueDistance = 10 *
vcl_sqrt( static_cast<double>(ImageDimension) );
FilterType::RealType distance = filter->GetDirectedHausdorffDistance();
std::cout << " True distance: " << trueDistance << std::endl;
std::cout << " Computed computed: " << distance << std::endl;
std::cout << " Average distance: " << filter->GetAverageHausdorffDistance() << std::endl;
if ( vnl_math_abs( trueDistance - distance ) > 0.1 )
{
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
if ( vnl_math_abs( 6.5 - filter->GetAverageHausdorffDistance() ) > 0.1 )
{
std::cout << "Test failed, average distance too great. " << std::endl;
return EXIT_FAILURE;
}
}
// compute the directed Hausdorff distance h(image2,image1)
{
typedef itk::DirectedHausdorffDistanceImageFilter<Image2Type,Image1Type> FilterType;
FilterType::Pointer filter = FilterType::New();
filter->SetInput1( image2 );
filter->SetInput2( image1 );
filter->Update();
// check results
FilterType::RealType trueDistance = 5 *
vcl_sqrt( static_cast<double>(ImageDimension) );
FilterType::RealType distance = filter->GetDirectedHausdorffDistance();
std::cout << " True distance: " << trueDistance << std::endl;
std::cout << " Computed computed: " << distance << std::endl;
std::cout << " Average distance: " << filter->GetAverageHausdorffDistance() << std::endl;
if ( vnl_math_abs( trueDistance - distance ) > 0.1 )
{
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
if ( vnl_math_abs( 2.5 - filter->GetAverageHausdorffDistance() ) > 0.1 )
{
std::cout << "Test failed, average distance too great. " << std::endl;
return EXIT_FAILURE;
}
}
// compute the Hausdorff distance H(image1,image2)
{
typedef itk::HausdorffDistanceImageFilter<Image1Type,Image2Type> FilterType;
FilterType::Pointer filter = FilterType::New();
filter->SetInput1( image1 );
filter->SetInput2( image2 );
filter->Update();
// check results
FilterType::RealType trueDistance = 10 *
vcl_sqrt( static_cast<double>(ImageDimension) );
FilterType::RealType distance = filter->GetHausdorffDistance();
std::cout << " True distance: " << trueDistance << std::endl;
std::cout << " Computed computed: " << distance << std::endl;
std::cout << " Average distance: " << filter->GetAverageHausdorffDistance() << std::endl;
if ( vnl_math_abs( trueDistance - distance ) > 0.1 )
{
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
if ( vnl_math_abs( 4.5 - filter->GetAverageHausdorffDistance() ) > 0.1 )
{
std::cout << "Test failed, average distance too great. " << std::endl;
return EXIT_FAILURE;
}
}
// compute the Hausdorff distance H(image2,image1)
{
typedef itk::HausdorffDistanceImageFilter<Image2Type,Image1Type> FilterType;
FilterType::Pointer filter = FilterType::New();
filter->SetInput1( image2 );
filter->SetInput2( image1 );
filter->Update();
// check results
FilterType::RealType trueDistance = 10 *
vcl_sqrt( static_cast<double>(ImageDimension) );
FilterType::RealType distance = filter->GetHausdorffDistance();
std::cout << " True distance: " << trueDistance << std::endl;
std::cout << " Computed computed: " << distance << std::endl;
std::cout << " Average distance: " << filter->GetAverageHausdorffDistance() << std::endl;
if ( vnl_math_abs( trueDistance - distance ) > 0.1 )
{
std::cout << "Test failed. " << std::endl;
return EXIT_FAILURE;
}
if ( vnl_math_abs( 4.5 - filter->GetAverageHausdorffDistance() ) > 0.1 )
{
std::cout << "Test failed, average distance too great. " << std::endl;
return EXIT_FAILURE;
}
}
std::cout << "Test passed. " << std::endl;
return EXIT_SUCCESS;
}
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