ITK/Examples/WishList/ImageProcessing/ColorNormalizedCorrelation: Difference between revisions

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This example extracts a patch from a color image and searches for it using normalized correlation. The output of the correlation filter is a correlation map. The maximum of this map is the "best" position of the query patch. We know the correct location because we extracted the patch from the image, so it will match exactly.
{{warning|1=The media wiki content on this page is no longer maintained. The examples presented on the https://itk.org/Wiki/* pages likely require ITK version 4.13 or earlier releasesIn many cases, the examples on this page no longer conform to the best practices for modern ITK versions.}}
 
==ColorNormalizedCorrelation.cxx==
<source lang="cpp">
#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkNormalizedCorrelationImageFilter.h"
#include "itkRegionOfInterestImageFilter.h"
#include "itkImageKernelOperator.h"
#include "itkRescaleIntensityImageFilter.h"
#include "itkImageFileWriter.h"
#include "itkMinimumMaximumImageCalculator.h"
#include "itkCovariantVector.h"
 
#include "QuickView.h"
 
#include <iostream>
#include <string>
 
// Vector types
typedef itk::CovariantVector<float, 3> FloatVectorType;
typedef itk::CovariantVector<unsigned char, 3> UnsignedCharVectorType;
 
// Vector image types
typedef itk::Image<FloatVectorType, 2> FloatVectorImageType;
typedef itk::Image<UnsignedCharVectorType, 2> UnsignedCharVectorImageType;
 
// Scalar image types
typedef itk::Image<float, 2> FloatImageType;
typedef itk::Image<unsigned char, 2> UnsignedCharImageType;
 
int main(int argc, char *argv[])
{
  if(argc < 2)
    {
    std::cerr << "Required: filename" << std::endl;
    return EXIT_FAILURE;
    }
 
  std::string filename = argv[1];
 
  typedef itk::ImageFileReader<FloatVectorImageType> ReaderType;
 
  // Read the image
  ReaderType::Pointer reader = ReaderType::New();
  reader->SetFileName(filename.c_str());
  reader->Update();
 
  // Extract a small region
  typedef itk::RegionOfInterestImageFilter< FloatVectorImageType,
                                            FloatVectorImageType > ExtractFilterType;
 
  ExtractFilterType::Pointer extractFilter = ExtractFilterType::New();
 
  FloatImageType::IndexType start;
  start.Fill(50);
 
   FloatImageType::SizeType patchSize;
  patchSize.Fill(51);
 
  FloatImageType::RegionType desiredRegion(start,patchSize);
 
  extractFilter->SetRegionOfInterest(desiredRegion);
  extractFilter->SetInput(reader->GetOutput());
  extractFilter->Update();
 
  // Perform normalized correlation
  // <input type, mask type (not used), output type>
  typedef itk::NormalizedCorrelationImageFilter<FloatVectorImageType, FloatVectorImageType, FloatImageType> CorrelationFilterType;
 
  itk::ImageKernelOperator<FloatVectorType> kernelOperator;
  kernelOperator.SetImageKernel(extractFilter->GetOutput());
 
  // The radius of the kernel must be the radius of the patch, NOT the size of the patch
  itk::Size<2> radius = extractFilter->GetOutput()->GetLargestPossibleRegion().GetSize();
  radius[0] = (radius[0]-1) / 2;
  radius[1] = (radius[1]-1) / 2;
 
  kernelOperator.CreateToRadius(radius);
 
  CorrelationFilterType::Pointer correlationFilter = CorrelationFilterType::New();
  correlationFilter->SetInput(reader->GetOutput());
  correlationFilter->SetTemplate(kernelOperator);
  correlationFilter->Update();
 
  typedef itk::MinimumMaximumImageCalculator <FloatImageType>
          MinimumMaximumImageCalculatorType;
 
  MinimumMaximumImageCalculatorType::Pointer minimumMaximumImageCalculatorFilter
          = MinimumMaximumImageCalculatorType::New ();
  minimumMaximumImageCalculatorFilter->SetImage(correlationFilter->GetOutput());
  minimumMaximumImageCalculatorFilter->Compute();
 
  itk::Index<2> maximumCorrelationPatchCenter = minimumMaximumImageCalculatorFilter->GetIndexOfMaximum();
  std::cout << "Maximum: " << maximumCorrelationPatchCenter << std::endl;
 
  // Note that the best correlation is at the center of the patch we extracted (ie. (75, 75) rather than the corner (50,50)
 
  typedef itk::RescaleIntensityImageFilter< FloatImageType, UnsignedCharImageType > RescaleFilterType;
  typedef itk::ImageFileWriter<UnsignedCharVectorImageType> WriterType;
  {
  RescaleFilterType::Pointer rescaleFilter = RescaleFilterType::New();
  rescaleFilter->SetInput(correlationFilter->GetOutput());
  rescaleFilter->SetOutputMinimum(0);
  rescaleFilter->SetOutputMaximum(255);
  rescaleFilter->Update();
 
  WriterType::Pointer writer = WriterType::New();
  writer->SetInput(rescaleFilter->GetOutput());
  writer->SetFileName("correlation.png");
  writer->Update();
  }
 
  {
  RescaleFilterType::Pointer rescaleFilter = RescaleVectorFilterType::New();
  rescaleFilter->SetInput(extractFilter->GetOutput());
  rescaleFilter->SetOutputMinimum(0);
  rescaleFilter->SetOutputMaximum(255);
  rescaleFilter->Update();
 
  WriterType::Pointer writer = WriterType::New();
  writer->SetInput(rescaleFilter->GetOutput());
  writer->SetFileName("patch.png");
  writer->Update();
  }
 
  // Extract the best matching patch
  FloatImageType::IndexType bestPatchStart;
  bestPatchStart[0] = maximumCorrelationPatchCenter[0] - radius[0];
  bestPatchStart[1] = maximumCorrelationPatchCenter[1] - radius[1];
 
  FloatImageType::RegionType bestPatchRegion(bestPatchStart,patchSize);
 
  ExtractFilterType::Pointer bestPatchExtractFilter = ExtractFilterType::New();
  bestPatchExtractFilter->SetRegionOfInterest(bestPatchRegion);
  bestPatchExtractFilter->SetInput(reader->GetOutput());
  bestPatchExtractFilter->Update();
 
  QuickView viewer;
  viewer.AddImage(reader->GetOutput());
  viewer.AddImage(extractFilter->GetOutput());
  viewer.AddImage(correlationFilter->GetOutput());
  viewer.AddImage(bestPatchExtractFilter->GetOutput());
  viewer.Visualize();
 
  return EXIT_SUCCESS;
}
 
</source>
 
{{ITKVTKCMakeLists|{{SUBPAGENAME}}}}

Latest revision as of 23:07, 7 June 2019

Warning: The media wiki content on this page is no longer maintained. The examples presented on the https://itk.org/Wiki/* pages likely require ITK version 4.13 or earlier releases. In many cases, the examples on this page no longer conform to the best practices for modern ITK versions.