ITK  4.9.0
Insight Segmentation and Registration Toolkit
WikiExamples/ImageProcessing/ScalarConnectedComponentImageFilter.cxx
#include "itkImage.h"
#include "itksys/SystemTools.hxx"
#include <sstream>
#include "QuickView.h"
template <typename TImage>
static void CreateImage(TImage* const image);
template<typename TImage, typename TLabelImage>
static void SummarizeLabelStatistics (TImage* image,
TLabelImage* labelImage);
int main( int argc, char *argv[])
{
const unsigned int Dimension = 2;
typedef short PixelType;
typedef itk::RGBPixel<unsigned char> RGBPixelType;
typedef unsigned int LabelPixelType;
ImageType::Pointer image;
PixelType distanceThreshold = 4;
if( argc < 2 )
{
image = ImageType::New();
CreateImage(image.GetPointer());
}
else
{
typedef itk::ImageFileReader<ImageType> ReaderType;
ReaderType::Pointer reader = ReaderType::New();
reader->SetFileName(argv[1]);
reader->Update();
if (argc > 2)
{
distanceThreshold = static_cast<PixelType> (atoi(argv[2]));
}
image = reader->GetOutput();
}
ConnectedComponentImageFilterType;
ConnectedComponentImageFilterType::Pointer connected =
ConnectedComponentImageFilterType::New ();
connected->SetInput(image);
connected->SetDistanceThreshold(distanceThreshold);
RelabelFilterType;
RelabelFilterType::Pointer relabel =
RelabelFilterType::New();
RelabelFilterType::ObjectSizeType minSize = 20;
if (argc > 3)
{
minSize = atoi(argv[3]);
}
relabel->SetInput(connected->GetOutput());
relabel->SetMinimumObjectSize(minSize);
relabel->Update();
SummarizeLabelStatistics (image.GetPointer(), relabel->GetOutput());
RGBFilterType::Pointer rgbFilter =
RGBFilterType::New();
rgbFilter->SetInput( relabel->GetOutput() );
QuickView viewer;
viewer.AddImage(
image.GetPointer(),true,
argc > 1 ? itksys::SystemTools::GetFilenameName(argv[1]) : "Generated image");
std::stringstream desc;
desc << "Scalar Connected Components:\n# of Objects: "
<< relabel->GetNumberOfObjects()
<< " Threshold: "
<< " Min Size: " << relabel->GetMinimumObjectSize();
viewer.AddRGBImage(
rgbFilter->GetOutput(),
true,
desc.str());
viewer.Visualize();
return EXIT_SUCCESS;
}
template <typename TImage>
void CreateImage(TImage* const image)
{
// Create an image with 2 connected components
typename TImage::IndexType start = {{0,0}};
start[0] = 0;
start[1] = 0;
typename TImage::SizeType size;
unsigned int NumRows = 200;
unsigned int NumCols = 300;
size[0] = NumRows;
size[1] = NumCols;
typename TImage::RegionType region(start, size);
image->SetRegions(region);
image->Allocate();
// Make a square
for(typename TImage::IndexValueType r = 20; r < 80; r++)
{
for(typename TImage::IndexValueType c = 30; c < 100; c++)
{
typename TImage::IndexType pixelIndex = {{r,c}};
image->SetPixel(pixelIndex, 255);
}
}
// Make another square
for(typename TImage::IndexValueType r = 100; r < 130; r++)
{
for(typename TImage::IndexValueType c = 115; c < 160; c++)
{
typename TImage::IndexType pixelIndex = {{r,c}};
image->SetPixel(pixelIndex, 255);
}
}
}
template<typename TImage, typename TLabelImage>
void SummarizeLabelStatistics (TImage* image,
TLabelImage* labelImage)
{
LabelStatisticsImageFilterType;
typename LabelStatisticsImageFilterType::Pointer labelStatisticsImageFilter =
LabelStatisticsImageFilterType::New();
labelStatisticsImageFilter->SetLabelInput( labelImage );
labelStatisticsImageFilter->SetInput(image);
labelStatisticsImageFilter->UseHistogramsOn(); // needed to compute median
labelStatisticsImageFilter->Update();
std::cout << "Number of labels: "
<< labelStatisticsImageFilter->GetNumberOfLabels() << std::endl;
std::cout << std::endl;
typedef typename LabelStatisticsImageFilterType::ValidLabelValuesContainerType ValidLabelValuesType;
typedef typename LabelStatisticsImageFilterType::LabelPixelType LabelPixelType;
for(typename ValidLabelValuesType::const_iterator vIt = labelStatisticsImageFilter->GetValidLabelValues().begin();
vIt != labelStatisticsImageFilter->GetValidLabelValues().end();
++vIt)
{
if ( labelStatisticsImageFilter->HasLabel(*vIt) )
{
LabelPixelType labelValue = *vIt;
std::cout << "Label: " << *vIt << std::endl;
std::cout << "\tmin: "
<< labelStatisticsImageFilter->GetMinimum( labelValue )
<< std::endl;
std::cout << "\tmax: "
<< labelStatisticsImageFilter->GetMaximum( labelValue )
<< std::endl;
std::cout << "\tmedian: "
<< labelStatisticsImageFilter->GetMedian( labelValue )
<< std::endl;
std::cout << "\tmean: "
<< labelStatisticsImageFilter->GetMean( labelValue )
<< std::endl;
std::cout << "\tsigma: "
<< labelStatisticsImageFilter->GetSigma( labelValue )
<< std::endl;
std::cout << "\tvariance: "
<< labelStatisticsImageFilter->GetVariance( labelValue )
<< std::endl;
std::cout << "\tsum: "
<< labelStatisticsImageFilter->GetSum( labelValue )
<< std::endl;
std::cout << "\tcount: "
<< labelStatisticsImageFilter->GetCount( labelValue )
<< std::endl;
std::cout << "\tregion: "
<< labelStatisticsImageFilter->GetRegion( labelValue )
<< std::endl;
}
}
}