ITK  5.2.0
Insight Toolkit
Examples/Filtering/DanielssonDistanceMapImageFilter.cxx
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* Copyright NumFOCUS
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* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
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// Software Guide : BeginCommandLineArgs
// INPUTS: {FivePointsDilated.png}
// OUTPUTS: {DanielssonDistanceMapImageFilterOutput1.png}
// OUTPUTS: {DanielssonDistanceMapImageFilterOutput2.png}
// ARGUMENTS: {DanielssonDistanceMapImageFilterOutput3.mhd}
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// This example illustrates the use of the
// \doxygen{DanielssonDistanceMapImageFilter}. This filter generates a
// distance map from the input image using the algorithm developed by
// Danielsson \cite{Danielsson1980}. As secondary outputs, a Voronoi
// partition of the input elements is produced, as well as a vector image
// with the components of the distance vector to the closest point. The input
// to the map is assumed to be a set of points on the input image. The label
// of each group of pixels is assigned by the
// \doxygen{ConnectedComponentImageFilter}.
//
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Instantiation}
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Header}
//
// The first step required to use this filter is to include its header file.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
#include "itkImage.h"
int
main(int argc, char * argv[])
{
if (argc < 5)
{
std::cerr << "Usage: " << argv[0];
std::cerr << " inputImageFile outputDistanceMapImageFile ";
std::cerr << " outputVoronoiMapImageFile ";
std::cerr << " outputVectorMapImageFile ";
std::cerr << std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Then we must decide what pixel types to use for the input and output
// images. Since the output will contain distances measured in pixels, the
// pixel type should be able to represent at least the width of the image,
// or said in $N$-dimensional terms, the maximum extension along all the
// dimensions. The input, output (distance map), and voronoi partition
// image types are now defined using their respective pixel type and
// dimension.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using InputPixelType = unsigned char;
using OutputPixelType = unsigned short;
using VoronoiPixelType = unsigned char;
using InputImageType = itk::Image<InputPixelType, 2>;
using OutputImageType = itk::Image<OutputPixelType, 2>;
using VoronoiImageType = itk::Image<VoronoiPixelType, 2>;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The filter type can be instantiated using the input and output image
// types defined above. A filter object is created with the \code{New()}
// method.
//
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!instantiation}
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!New()}
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!Pointer}
//
// Software Guide : EndLatex
using LabelerType =
LabelerType::Pointer labeler = LabelerType::New();
// Software Guide : BeginCodeSnippet
using FilterType = itk::DanielssonDistanceMapImageFilter<InputImageType,
OutputImageType,
VoronoiImageType>;
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
using RescalerType =
RescalerType::Pointer scaler = RescalerType::New();
using VoronoiRescalerType =
VoronoiRescalerType::Pointer voronoiScaler = VoronoiRescalerType::New();
//
// Reader and Writer types are instantiated.
//
using VoronoiWriterType = itk::ImageFileWriter<VoronoiImageType>;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
VoronoiWriterType::Pointer voronoiWriter = VoronoiWriterType::New();
reader->SetFileName(argv[1]);
writer->SetFileName(argv[2]);
voronoiWriter->SetFileName(argv[3]);
// Software Guide : BeginLatex
//
// The input to the filter is taken from a reader and its output is passed
// to a \doxygen{RescaleIntensityImageFilter} and then to a writer. The
// scaler and writer are both templated over the image type, so we
// instantiate a separate pipeline for the voronoi partition map starting
// at the scaler.
//
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!SetInput()}
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!GetOutput()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
labeler->SetInput(reader->GetOutput());
filter->SetInput(labeler->GetOutput());
scaler->SetInput(filter->GetOutput());
writer->SetInput(scaler->GetOutput());
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The Voronoi map is obtained with the \code{GetVoronoiMap()} method. In
// the lines below we connect this output to the intensity rescaler.
//
// \index{itk::Danielsson\-Distance\-Map\-Image\-Filter!GetVoronoiMap()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
voronoiScaler->SetInput(filter->GetVoronoiMap());
voronoiWriter->SetInput(voronoiScaler->GetOutput());
// Software Guide : EndCodeSnippet
scaler->SetOutputMaximum(65535L);
scaler->SetOutputMinimum(0L);
voronoiScaler->SetOutputMaximum(255);
voronoiScaler->SetOutputMinimum(0);
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.32\textwidth]{FivePointsDilated}
// \includegraphics[width=0.32\textwidth]{DanielssonDistanceMapImageFilterOutput1}
// \includegraphics[width=0.32\textwidth]{DanielssonDistanceMapImageFilterOutput2}
// \itkcaption[DanielssonDistanceMapImageFilter
// output]{DanielssonDistanceMapImageFilter output. Set of pixels, distance
// map and Voronoi partition.}
// \label{fig:DanielssonDistanceMapImageFilterInputOutput}
// \end{figure}
//
// Figure \ref{fig:DanielssonDistanceMapImageFilterInputOutput} illustrates
// the effect of this filter on a binary image with a set of points. The
// input image is shown at the left, and the distance map at the center and
// the Voronoi partition at the right. This filter computes distance maps
// in N-dimensions and is therefore capable of producing $N$-dimensional
// Voronoi partitions.
//
// \index{Voronoi partitions}
// \index{Voronoi partitions!itk::Danielsson\-Distance\-Map\-Image\-Filter}
//
// Software Guide : EndLatex
writer->Update();
voronoiWriter->Update();
// Software Guide : BeginLatex
//
// The distance filter also produces an image of \doxygen{Offset} pixels
// representing the vectorial distance to the closest object in the scene.
// The type of this output image is defined by the VectorImageType
// trait of the filter type.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using OffsetImageType = FilterType::VectorImageType;
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We can use this type for instantiating an \doxygen{ImageFileWriter} type
// and creating an object of this class in the following lines.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using WriterOffsetType = itk::ImageFileWriter<OffsetImageType>;
WriterOffsetType::Pointer offsetWriter = WriterOffsetType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The output of the distance filter can be connected as input to the
// writer.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
offsetWriter->SetInput(filter->GetVectorDistanceMap());
// Software Guide : EndCodeSnippet
offsetWriter->SetFileName(argv[4]);
// Software Guide : BeginLatex
//
// Execution of the writer is triggered by the invocation of the
// \code{Update()} method. Since this method can potentially throw
// exceptions it must be placed in a \code{try/catch} block.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
try
{
offsetWriter->Update();
}
catch (const itk::ExceptionObject & exp)
{
std::cerr << "Exception caught !" << std::endl;
std::cerr << exp << std::endl;
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Note that only the \doxygen{MetaImageIO} class supports reading and
// writing images of pixel type \doxygen{Offset}.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
itkImageFileReader.h
itkImage.h
itk::ImageFileReader
Data source that reads image data from a single file.
Definition: itkImageFileReader.h:75
itk::DanielssonDistanceMapImageFilter
This filter computes the distance map of the input image as an approximation with pixel accuracy to t...
Definition: itkDanielssonDistanceMapImageFilter.h:59
itk::ImageFileWriter
Writes image data to a single file.
Definition: itkImageFileWriter.h:87
itkRescaleIntensityImageFilter.h
itkImageFileWriter.h
itkDanielssonDistanceMapImageFilter.h
itkConnectedComponentImageFilter.h
itk::RescaleIntensityImageFilter
Applies a linear transformation to the intensity levels of the input Image.
Definition: itkRescaleIntensityImageFilter.h:154
itk::Image
Templated n-dimensional image class.
Definition: itkImage.h:86
itk::ConnectedComponentImageFilter
Label the objects in a binary image.
Definition: itkConnectedComponentImageFilter.h:59