Examples/Filtering/CannyEdgeDetectionImageFilter.cxx

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//  Software Guide : BeginLatex
//
//  This example introduces the use of the
//  \doxygen{CannyEdgeDetectionImageFilter}. Canny edge detection is widely used for
//  edge detection since it is the optimal solution satisfying the constraints
//  of good sensitivity, localization and noise robustness.  To achieve this
//  end, Canny edge detection is implemented internally as a multi-stage
//  algorithm, which involves Gaussian smoothing to remove noise, calculation
//  of gradient magnitudes to localize edge features, non-maximum suppression
//  to remove suprious features, and finally thresholding to yield a binary image.
//  Though the specifics of this internal pipeline are largely abstracted from
//  the user of the class, it is nonetheless beneficial to have a general
//  understanding of these components so that parameters can be appropriately
//  adjusted.
//
//  \index{itk::CannyEdgeDetectionImageFilter|textbf}
//
//  The first step required for using this filter is to include its header file.
//
//  \index{itk::CannyEdgeDetectionImageFilter!header}
//
//  Software Guide : EndLatex

#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkCastImageFilter.h"
#include "itkRescaleIntensityImageFilter.h"

// Software Guide : BeginCodeSnippet
#include "itkCannyEdgeDetectionImageFilter.h"
// Software Guide : EndCodeSnippet

int main(int argc, char* argv[])
{

  if( argc < 3 )
    {
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0]
              << " inputImage outputImage"
              << " [variance upperThreshold lowerThreshold]" << std::endl;
    return EXIT_FAILURE;
    }

  const char * inputFilename  = argv[1];
  const char * outputFilename = argv[2];

  float variance = 2.0;
  float upperThreshold = 0.0;
  float lowerThreshold = 0.0;

  if( argc > 3 )
    {
    variance = std::stod( argv[3] );
    }

  if( argc > 4 )
    {
    upperThreshold = std::stod( argv[4] );
    }

  if( argc > 5 )
    {
    lowerThreshold = std::stod( argv[5] );
    }

  std::cout << "Variance = " << variance << std::endl;
  std::cout << "UpperThreshold = " << upperThreshold << std::endl;
  std::cout << "LowerThreshold = " << lowerThreshold << std::endl;

  //  Software Guide : BeginLatex
  //
  //  In this example, images are read and written with \code{unsigned char}
  //  pixel type.  However, Canny edge detection requires floating point
  //  pixel types in order to avoid numerical errors.  For this reason,
  //  a separate internal image type with pixel type \code{double} is defined
  //  for edge detection.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  constexpr unsigned int Dimension = 2;
  using CharPixelType = unsigned char;  //  IO
  using RealPixelType = double;  //  Operations

  using CharImageType = itk::Image< CharPixelType, Dimension >;
  using RealImageType = itk::Image< RealPixelType, Dimension >;

  //  Software Guide : EndCodeSnippet

  using ReaderType = itk::ImageFileReader< CharImageType >;
  using WriterType = itk::ImageFileWriter< CharImageType >;

  //  Software Guide : BeginLatex
  //
  //  The \code{CharImageType} image is cast to and from \code{RealImageType}
  //  using \doxygen{CastImageFilter} and \code{RescaleIntensityImageFilter},
  //  respectively; both the input and output of \code{CannyEdgeDetectionImageFilter}
  //  are \code{RealImageType}.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  using CastToRealFilterType =
    itk::CastImageFilter< CharImageType, RealImageType >;
  using CannyFilterType =
    itk::CannyEdgeDetectionImageFilter< RealImageType, RealImageType >;
  using RescaleFilterType =
    itk::RescaleIntensityImageFilter< RealImageType, CharImageType >;

  //  Software Guide : EndCodeSnippet

  //Setting the IO

  ReaderType::Pointer           reader      = ReaderType::New();
  CastToRealFilterType::Pointer toReal      = CastToRealFilterType::New();
  CannyFilterType::Pointer      cannyFilter = CannyFilterType::New();
  RescaleFilterType::Pointer    rescale     = RescaleFilterType::New();
  WriterType::Pointer           writer      = WriterType::New();

  reader->SetFileName( inputFilename  );
  writer->SetFileName( outputFilename );

  toReal->SetInput( reader->GetOutput() );
  cannyFilter->SetInput( toReal->GetOutput() );
  rescale->SetInput( cannyFilter->GetOutput() );
  writer->SetInput( rescale->GetOutput() );

  //  Software Guide : BeginLatex
  //
  //  In this example, three parameters of the Canny edge detection
  //  filter may be set via the \code{SetVariance()}, \code{SetUpperThreshold()},
  //  and \code{SetLowerThreshold()} methods.  Based on the previous discussion
  //  of the steps in the internal pipeline, we understand that
  //  \code{variance} adjusts the amount of Gaussian smoothing and
  //  \code{upperThreshold} and \code{lowerThreshold} control which edges are
  //  selected in the final step.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  cannyFilter->SetVariance( variance );
  cannyFilter->SetUpperThreshold( upperThreshold );
  cannyFilter->SetLowerThreshold( lowerThreshold );

  //  Software Guide : EndCodeSnippet

  //  Software Guide : BeginLatex
  //
  //  Finally, \code{Update()} is called on \code{writer} to trigger excecution
  //  of the pipeline.  As usual, the call is wrapped in a \code{try/catch}
  //  block.
  //
  //  Software Guide : EndLatex

  //  Software Guide : BeginCodeSnippet
  try
    {
    writer->Update();
    }
  catch( itk::ExceptionObject & err )
    {
    std::cout << "ExceptionObject caught !" << std::endl;
    std::cout << err << std::endl;
    return EXIT_FAILURE;
    }

  // Software Guide : EndCodeSnippet

  return EXIT_SUCCESS;

}