Examples/Filtering/MathematicalMorphologyBinaryFilters.cxx

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//  Software Guide : BeginCommandLineArgs
//    INPUTS: {BrainProtonDensitySlice.png}
//    OUTPUTS: {MathematicalMorphologyBinaryErosionOutput.png}
//    OUTPUTS: {MathematicalMorphologyBinaryDilationOutput.png}
//    ARGUMENTS:    150 180
//  Software Guide : EndCommandLineArgs
 
//  Software Guide : BeginLatex
//
//  The following section illustrates the use of filters that perform basic
//  mathematical morphology operations on binary images. The
//  \doxygen{BinaryErodeImageFilter} and \doxygen{BinaryDilateImageFilter} are
//  described here. The filter names clearly specify the type of image on
//  which they operate.  The header files required to construct a simple
//  example of the use of the mathematical morphology filters are included
//  below.
//
//  \index{itk::BinaryDilateImageFilter!header}
//  \index{itk::BinaryErodeImageFilter!header}
//
//  Software Guide : EndLatex
 
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
 
 
// Software Guide : BeginCodeSnippet
#include "itkBinaryErodeImageFilter.h"
#include "itkBinaryDilateImageFilter.h"
#include "itkBinaryBallStructuringElement.h"
// Software Guide : EndCodeSnippet
 
#include "itkBinaryThresholdImageFilter.h"
 
 
int
main(int argc, char * argv[])
{
  if (argc < 6)
  {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << "  inputImageFile  ";
    std::cerr << " outputImageFileErosion  outputImageFileDilation";
    std::cerr << " lowerThreshold upperThreshold " << std::endl;
    return EXIT_FAILURE;
  }
 
 
  //  Software Guide : BeginLatex
  //
  //  The following code defines the input and output pixel types and their
  //  associated image types.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  constexpr unsigned int Dimension = 2;
 
  using InputPixelType = unsigned char;
  using OutputPixelType = unsigned char;
 
  using InputImageType = itk::Image<InputPixelType, Dimension>;
  using OutputImageType = itk::Image<OutputPixelType, Dimension>;
  // Software Guide : EndCodeSnippet
 
  using ReaderType = itk::ImageFileReader<InputImageType>;
  using WriterType = itk::ImageFileWriter<OutputImageType>;
 
 
  using ThresholdFilterType =
    itk::BinaryThresholdImageFilter<InputImageType, InputImageType>;
 
 
  //  Software Guide : BeginLatex
  //
  //  Mathematical morphology operations are implemented by applying an
  //  operator over the neighborhood of each input pixel. The combination of
  //  the rule and the neighborhood is known as \emph{structuring
  //  element}. Although some rules have become defacto standards for image
  //  processing, there is a good deal of freedom as to what kind of
  //  algorithmic rule should be applied to the neighborhood. The
  //  implementation in ITK follows the typical rule of minimum for
  //  erosion and maximum for dilation.
  //
  //  The structuring element is implemented as a NeighborhoodOperator. In
  //  particular, the default structuring element is the
  //  \doxygen{BinaryBallStructuringElement} class. This class is instantiated
  //  using the pixel type and dimension of the input image.
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  using StructuringElementType =
    itk::BinaryBallStructuringElement<InputPixelType, Dimension>;
  // Software Guide : EndCodeSnippet
 
  //  Software Guide : BeginLatex
  //
  //  The structuring element type is then used along with the input and
  //  output image types for instantiating the type of the filters.
  //
  //  Software Guide : EndLatex
 
 
  // Software Guide : BeginCodeSnippet
  using ErodeFilterType = itk::BinaryErodeImageFilter<InputImageType,
                                                      OutputImageType,
                                                      StructuringElementType>;
 
  using DilateFilterType =
    itk::BinaryDilateImageFilter<InputImageType,
                                 OutputImageType,
                                 StructuringElementType>;
  // Software Guide : EndCodeSnippet
 
 
  // Creation of Reader and Writer filters
  auto reader = ReaderType::New();
  auto writerDilation = WriterType::New();
  auto writerErosion = WriterType::New();
 
  auto thresholder = ThresholdFilterType::New();
 
  //  Software Guide : BeginLatex
  //
  //  The filters can now be created by invoking the \code{New()} method and
  //  assigning the result to \doxygen{SmartPointer}s.
  //
  //  \index{itk::BinaryDilateImageFilter!New()}
  //  \index{itk::BinaryErodeImageFilter!New()}
  //  \index{itk::BinaryDilateImageFilter!Pointer}
  //  \index{itk::BinaryErodeImageFilter!Pointer}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  auto binaryErode = ErodeFilterType::New();
  auto binaryDilate = DilateFilterType::New();
  // Software Guide : EndCodeSnippet
 
  //  Software Guide : BeginLatex
  //
  //  The structuring element is not a reference counted class. Thus it is
  //  created as a C++ stack object instead of using \code{New()} and
  //  SmartPointers. The radius of the neighborhood associated with the
  //  structuring element is defined with the \code{SetRadius()} method and
  //  the \code{CreateStructuringElement()} method is invoked in order to
  //  initialize the operator.  The resulting structuring element is passed to
  //  the mathematical morphology filter through the \code{SetKernel()}
  //  method, as illustrated below.
  //
  //  \index{itk::BinaryBallStructuringElement!SetRadius()}
  //  \index{itk::BinaryBallStructuringElement!CreateStructuringElement()}
  //  \index{itk::BinaryDilateImageFilter!SetKernel()}
  //  \index{itk::BinaryErodeImageFilter!SetKernel()}
  //  \index{SetRadius()!itk::BinaryBallStructuringElement}
  //  \index{SetKernel()!itk::BinaryDilateImageFilter}
  //  \index{SetKernel()!itk::BinaryErodeImageFilter}
  //  \index{SetRadius()!itk::BinaryBallStructuringElement}
  //  \index{CreateStructuringElement()!itk::BinaryBallStructuringElement}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  StructuringElementType structuringElement;
 
  structuringElement.SetRadius(1); // 3x3 structuring element
 
  structuringElement.CreateStructuringElement();
 
  binaryErode->SetKernel(structuringElement);
  binaryDilate->SetKernel(structuringElement);
  // Software Guide : EndCodeSnippet
 
 
  reader->SetFileName(argv[1]);
 
  writerErosion->SetFileName(argv[2]);
  writerDilation->SetFileName(argv[3]);
 
 
  //  Software Guide : BeginLatex
  //
  //  A binary image is provided as input to the filters. This image might be,
  //  for example, the output of a binary threshold image filter.
  //
  //  Software Guide : EndLatex
 
  const InputPixelType lowerThreshold = std::stoi(argv[4]);
  const InputPixelType upperThreshold = std::stoi(argv[5]);
 
  // Software Guide : BeginCodeSnippet
  thresholder->SetInput(reader->GetOutput());
 
  constexpr InputPixelType background = 0;
  constexpr InputPixelType foreground = 255;
 
  thresholder->SetOutsideValue(background);
  thresholder->SetInsideValue(foreground);
 
  thresholder->SetLowerThreshold(lowerThreshold);
  thresholder->SetUpperThreshold(upperThreshold);
  // Software Guide : EndCodeSnippet
 
 
  // Software Guide : BeginCodeSnippet
  binaryErode->SetInput(thresholder->GetOutput());
  binaryDilate->SetInput(thresholder->GetOutput());
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The values that correspond to ``objects'' in the binary image are
  //  specified with the methods \code{SetErodeValue()} and
  //  \code{SetDilateValue()}. The value passed to these methods will be
  //  considered the value over which the dilation and erosion rules will
  //  apply.
  //
  //  \index{itk::BinaryDilateImageFilter!SetDilateValue()}
  //  \index{itk::BinaryErodeImageFilter!SetErodeValue()}
  //  \index{SetDilateValue()!itk::BinaryDilateImageFilter}
  //  \index{SetErodeValue()!itk::BinaryErodeImageFilter}
  //
  //  Software Guide : EndLatex
 
  // Software Guide : BeginCodeSnippet
  binaryErode->SetErodeValue(foreground);
  binaryDilate->SetDilateValue(foreground);
  // Software Guide : EndCodeSnippet
 
 
  //  Software Guide : BeginLatex
  //
  //  The filter is executed by invoking its \code{Update()} method, or by
  //  updating any downstream filter, such as an image writer.
  //
  //  \index{itk::BinaryDilateImageFilter!Update()}
  //  \index{itk::BinaryErodeImageFilter!Update()}
  //
  //  Software Guide : EndLatex
 
 
  // Software Guide : BeginCodeSnippet
  writerDilation->SetInput(binaryDilate->GetOutput());
  writerDilation->Update();
  // Software Guide : EndCodeSnippet
 
  writerErosion->SetInput(binaryErode->GetOutput());
  writerErosion->Update();
 
  //  Software Guide : BeginLatex
  //
  // \begin{figure}
  // \center
  // \includegraphics[width=0.32\textwidth]{BinaryThresholdImageFilterOutput}
  // \includegraphics[width=0.32\textwidth]{MathematicalMorphologyBinaryErosionOutput}
  // \includegraphics[width=0.32\textwidth]{MathematicalMorphologyBinaryDilationOutput}
  // \itkcaption[Effect of erosion and dilation in a binary image.]{Effect of
  // erosion and dilation in a binary image.}
  // \label{fig:MathematicalMorphologyBinaryFilters}
  // \end{figure}
  //
  //  Figure \ref{fig:MathematicalMorphologyBinaryFilters} illustrates the
  //  effect of the erosion and dilation filters on a binary image from a MRI
  //  brain slice. The figure shows how these operations can be used to remove
  //  spurious details from segmented images.
  //
  //  Software Guide : EndLatex
 
 
  return EXIT_SUCCESS;
}