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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: VotingBinaryHoleFillingImageFilter.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
#ifdef __BORLANDC__
#define ITK_LEAN_AND_MEAN
#endif
// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput1.png}
// 1 1
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput2.png}
// 2 2
// Software Guide : EndCommandLineArgs
// Software Guide : BeginCommandLineArgs
// INPUTS: {BinaryThresholdImageFilterOutput.png}
// OUTPUTS: {VotingBinaryHoleFillingImageFilterOutput3.png}
// 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"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
// Software Guide : BeginLatex
//
// The header file corresponding to this filter should be included first.
//
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!header}
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
#include "itkVotingBinaryHoleFillingImageFilter.h"
// Software Guide : EndCodeSnippet
int main( int argc, char * argv[] )
{
if( argc < 4 )
{
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile radiusX radiusY" << 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
typedef unsigned char InputPixelType;
typedef unsigned char OutputPixelType;
typedef itk::Image< InputPixelType, 2 > InputImageType;
typedef itk::Image< OutputPixelType, 2 > OutputImageType;
// Software Guide : EndCodeSnippet
typedef itk::ImageFileReader< InputImageType > ReaderType;
typedef itk::ImageFileWriter< OutputImageType > WriterType;
ReaderType::Pointer reader = ReaderType::New();
WriterType::Pointer writer = WriterType::New();
reader->SetFileName( argv[1] );
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
typedef itk::VotingBinaryHoleFillingImageFilter<
InputImageType, OutputImageType > 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!Radius}
// \index{itk::Voting\-Binary\-Hole\-Filling\-Image\-Filter!Neighborhood}
//
// Software Guide : EndLatex
const unsigned int radiusX = atoi( argv[3] );
const unsigned int radiusY = atoi( argv[4] );
// Software Guide : BeginCodeSnippet
InputImageType::SizeType indexRadius;
indexRadius[0] = radiusX; // radius along x
indexRadius[1] = radiusY; // radius along y
filter->SetRadius( indexRadius );
// 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 or 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
filter->SetInput( reader->GetOutput() );
writer->SetInput( filter->GetOutput() );
writer->Update();
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// \begin{figure}
// \center
// \includegraphics[width=0.44\textwidth]{BinaryThresholdImageFilterOutput.eps}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput1.eps}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput2.eps}
// \includegraphics[width=0.44\textwidth]{VotingBinaryHoleFillingImageFilterOutput3.eps}
// \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;
}
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