ITK  5.2.0 Insight Toolkit
Examples/Filtering/VotingBinaryHoleFillingImageFilter.cxx
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// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput1.png}
// ARGUMENTS: 1 1
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput2.png}
// ARGUMENTS: 2 2
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput3.png}
// ARGUMENTS: 3 3
// Software Guide : EndCommandLineArgs
// Software Guide : BeginLatex
//
// The \doxygen{VotingBinaryHoleFillingImageFilter} applies a voting
// operation in order to fill in cavities. This can be used for smoothing
// contours and for filling holes in binary images.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter}
//
// Software Guide : EndLatex
#include "itkImage.h"
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int
main(int argc, char * argv[])
{
if (argc < 4)
{
std::cerr << "Usage: " << std::endl;
<< std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Then the pixel and image types of the input and output must be defined.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using InputPixelType = unsigned char;
using OutputPixelType = unsigned char;
using InputImageType = itk::Image<InputPixelType, 2>;
using OutputImageType = itk::Image<OutputPixelType, 2>;
// Software Guide : EndCodeSnippet
WriterType::Pointer writer = WriterType::New();
writer->SetFileName(argv[2]);
// Software Guide : BeginLatex
//
// Using the image types, it is now possible to define the filter type
// and create the filter object.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!instantiation}
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!New()}
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!Pointer}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using FilterType =
FilterType::Pointer filter = FilterType::New();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The size of the neighborhood is defined along every dimension by
// passing a \code{SizeType} object with the corresponding values. The
// value on each dimension is used as the semi-size of a rectangular
// box. For example, in $2D$ a size of $$1,2$$ will result in a $3 \times // 5$ neighborhood.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!Neighborhood}
//
// Software Guide : EndLatex
const unsigned int radiusX = std::stoi(argv[3]);
const unsigned int radiusY = std::stoi(argv[4]);
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Since the filter is expecting a binary image as input, we must specify
// the levels that are going to be considered background and foreground.
// This is done with the \code{SetForegroundValue()} and
// \code{SetBackgroundValue()} methods.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!SetForegroundValue()}
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!SetBackgroundValue()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetBackgroundValue(0);
filter->SetForegroundValue(255);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// We must also specify the majority threshold that is going to be used as
// the decision criterion for converting a background pixel into a
// foreground pixel. The rule of conversion is that a background pixel will
// be converted into a foreground pixel if the number of foreground
// neighbors surpass the number of background neighbors by the majority
// value. For example, in a 2D image, with neighborhood of radius 1, the
// neighborhood will have size $3 \times 3$. If we set the majority value
// to 2, then we are requiring that the number of foreground neighbors
// should be at least (3x3 -1 )/2 + majority. This is done with the
// \code{SetMajorityThreshold()} method.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!SetMajorityThreshold()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
filter->SetMajorityThreshold(2);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The input to the filter can be taken from any other filter, for example
// a reader. The output can be passed down the pipeline to other filters,
// for example, a writer. An update call on any downstream filter will
// trigger the execution of the median filter.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!SetInput()}
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!GetOutput()}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
writer->SetInput(filter->GetOutput());
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.44\textwidth]{BinaryThresholdImageFilterOutput}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput1}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput2}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput3}
// \itkcaption[Effect of the VotingBinaryHoleFilling filter.]{Effect of the
// VotingBinaryHoleFillingImageFilter on a slice from a MRI proton density
// brain image that has been thresholded in order to produce a binary image.
// The output images have used radius 1,2 and 3 respectively.}
// \label{fig:VotingBinaryHoleFillingImageFilterOutput}
// \end{figure}
//
// Figure \ref{fig:VotingBinaryHoleFillingImageFilterOutput} illustrates
// the effect of the VotingBinaryHoleFillingImageFilter filter on a
// thresholded slice of MRI brain image using neighborhood radii of
// $$1,1$$, $$2,2$$ and $$3,3$$ that correspond respectively to
// neighborhoods of size $3 \times 3$, $5 \times 5$, $7 \times 7$.
// The filtered image demonstrates the capability of this filter for
// reducing noise both in the background and foreground of the image, as
// well as smoothing the contours of the regions.
//
// Software Guide : EndLatex
return EXIT_SUCCESS;
}
itk::VotingBinaryHoleFillingImageFilter
Fills in holes and cavities by applying a voting operation on each pixel.
Definition: itkVotingBinaryHoleFillingImageFilter.h:42
itk::GTest::TypedefsAndConstructors::Dimension2::SizeType
ImageBaseType::SizeType SizeType
Definition: itkGTestTypedefsAndConstructors.h:49
itkImage.h