ITK  6.0.0
Insight Toolkit
Examples/Iterators/ShapedNeighborhoodIterators1.cxx
/*=========================================================================
*
* Copyright NumFOCUS
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
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*=========================================================================*/
#include <cmath>
// Software Guide : BeginLatex
//
// This example uses \doxygen{ShapedNeighborhoodIterator} to implement a
// binary erosion algorithm. If we think of an image $I$ as a set of pixel
// indices, then erosion of $I$ by a smaller set $E$, called the
// \emph{structuring element}, is the set of all indices at locations $x$ in
// $I$ such that when $E$ is positioned at $x$, every element in $E$ is also
// contained in $I$.
//
// This type of algorithm is easy to implement with shaped neighborhood
// iterators because we can use the iterator itself as the structuring element
// $E$ and move it sequentially through all positions $x$. The result at $x$
// is obtained by checking values in a simple iteration loop through the
// neighborhood stencil.
//
// We need two iterators, a shaped iterator for the input image and a regular
// image iterator for writing results to the output image.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Software Guide : EndCodeSnippet
int
main(int argc, char ** argv)
{
if (argc < 4)
{
std::cerr << "Missing parameters. " << std::endl;
std::cerr << "Usage: " << std::endl;
std::cerr << argv[0] << " inputImageFile outputImageFile element_radius"
<< std::endl;
return EXIT_FAILURE;
}
// Software Guide : BeginLatex
//
// Since we are working with binary images in this example, an
// \code{unsigned char} pixel type will do. The image and iterator types
// are defined using the pixel type.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using PixelType = unsigned char;
using ImageType = itk::Image<PixelType, 2>;
using ShapedNeighborhoodIteratorType =
// Software Guide : EndCodeSnippet
using ReaderType = itk::ImageFileReader<ImageType>;
auto reader = ReaderType::New();
reader->SetFileName(argv[1]);
try
{
reader->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
auto output = ImageType::New();
output->SetRegions(reader->GetOutput()->GetRequestedRegion());
output->Allocate();
// Software Guide : BeginLatex
//
// Refer to the examples in Section~\ref{sec:itkNeighborhoodIterator} or the
// source code of this example for a description of how to read the input
// image and allocate a matching output image.
//
// The size of the structuring element is read from the command line and
// used to define a radius for the shaped neighborhood iterator. Using the
// method developed in section~\ref{sec:itkNeighborhoodIterator} to minimize
// bounds checking, the iterator itself is not initialized until entering
// the main processing loop.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
unsigned int element_radius = std::stoi(argv[3]);
ShapedNeighborhoodIteratorType::RadiusType radius;
radius.Fill(element_radius);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The face calculator object introduced in
// Section~\ref{sec:NeighborhoodExample3} is created and used as before.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
using FaceCalculatorType =
FaceCalculatorType faceCalculator;
FaceCalculatorType::FaceListType faceList;
FaceCalculatorType::FaceListType::iterator fit;
faceList =
faceCalculator(reader->GetOutput(), output->GetRequestedRegion(), radius);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// Now we initialize some variables and constants.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
IteratorType out;
constexpr PixelType background_value = 0;
constexpr PixelType foreground_value = 255;
const auto rad = static_cast<float>(element_radius);
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The outer loop of the algorithm is structured as in previous neighborhood
// iterator examples. Each region in the face list is processed in turn. As
// each new region is processed, the input and output iterators are
// initialized on that region.
//
// The shaped iterator that ranges over the input is our structuring element
// and its active stencil must be created accordingly. For this example,
// the structuring element is shaped like a circle of radius
// \code{element\_radius}. Each of the appropriate neighborhood offsets is
// activated in the double \code{for} loop.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
for (fit = faceList.begin(); fit != faceList.end(); ++fit)
{
ShapedNeighborhoodIteratorType it(radius, reader->GetOutput(), *fit);
out = IteratorType(output, *fit);
// Creates a circular structuring element by activating all the pixels
// less than radius distance from the center of the neighborhood.
for (float y = -rad; y <= rad; ++y)
{
for (float x = -rad; x <= rad; ++x)
{
ShapedNeighborhoodIteratorType::OffsetType off;
float dis = std::sqrt(x * x + y * y);
if (dis <= rad)
{
off[0] = static_cast<int>(x);
off[1] = static_cast<int>(y);
it.ActivateOffset(off);
}
}
}
// Software Guide : EndCodeSnippet
// Software Guide : BeginLatex
//
// The inner loop, which implements the erosion algorithm, is fairly
// simple. The \code{for} loop steps the input and output iterators
// through their respective images. At each step, the active stencil of
// the shaped iterator is traversed to determine whether all pixels
// underneath the stencil contain the foreground value, i.e. are contained
// within the set $I$. Note the use of the stencil iterator, \code{ci},
// in performing this check.
//
// Software Guide : EndLatex
// Software Guide : BeginCodeSnippet
// Implements erosion
for (it.GoToBegin(), out.GoToBegin(); !it.IsAtEnd(); ++it, ++out)
{
ShapedNeighborhoodIteratorType::ConstIterator ci;
bool flag = true;
for (ci = it.Begin(); ci != it.End(); ++ci)
{
if (ci.Get() == background_value)
{
flag = false;
break;
}
}
if (flag == true)
{
out.Set(foreground_value);
}
else
{
out.Set(background_value);
}
}
}
// Software Guide : EndCodeSnippet
using WriterType = itk::ImageFileWriter<ImageType>;
auto writer = WriterType::New();
writer->SetFileName(argv[2]);
writer->SetInput(output);
try
{
writer->Update();
}
catch (const itk::ExceptionObject & err)
{
std::cerr << "ExceptionObject caught !" << std::endl;
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
itk::NeighborhoodAlgorithm::ImageBoundaryFacesCalculator
Splits an image into a main region and several "face" regions which are used to handle computations o...
Definition: itkNeighborhoodAlgorithm.h:63
itkConstShapedNeighborhoodIterator.h
itkNeighborhoodAlgorithm.h
itkImageFileReader.h
itkImageRegionIterator.h
itk::ImageFileReader
Data source that reads image data from a single file.
Definition: itkImageFileReader.h:75
itk::ImageRegionIterator
A multi-dimensional iterator templated over image type that walks a region of pixels.
Definition: itkImageRegionIterator.h:80
itk::ImageFileWriter
Writes image data to a single file.
Definition: itkImageFileWriter.h:90
itk::ConstShapedNeighborhoodIterator
Const version of ShapedNeighborhoodIterator, defining iteration of a local N-dimensional neighborhood...
Definition: itkConstShapedNeighborhoodIterator.h:72
itkImageFileWriter.h
itk::Image
Templated n-dimensional image class.
Definition: itkImage.h:88
New
static Pointer New()