From 6d6b25fec297f18dc45043f780a320d4e55607d0 Mon Sep 17 00:00:00 2001
From: Jordi Inglada <jordi.inglada@orfeo-toolbox.org>
Date: Wed, 14 Jun 2006 15:09:28 +0000
Subject: [PATCH] Nouveaux exemples segmentation
---
.../otbComplexMomentImageFunction.txx | 4 +-
Code/FeatureExtraction/otbHuImageFunction.txx | 9 +-
Examples/Segmentation/CMakeLists.txt | 12 +-
.../NeighborhoodConnectedImageFilter.cxx | 342 ++++++++++++++++++
.../OtsuMultipleThresholdImageFilter.cxx | 195 ++++++++++
.../Segmentation/OtsuThresholdImageFilter.cxx | 231 ++++++++++++
6 files changed, 788 insertions(+), 5 deletions(-)
create mode 100644 Examples/Segmentation/NeighborhoodConnectedImageFilter.cxx
create mode 100755 Examples/Segmentation/OtsuMultipleThresholdImageFilter.cxx
create mode 100755 Examples/Segmentation/OtsuThresholdImageFilter.cxx
diff --git a/Code/FeatureExtraction/otbComplexMomentImageFunction.txx b/Code/FeatureExtraction/otbComplexMomentImageFunction.txx
index 1f67679df3..a9ef0f2bc7 100644
--- a/Code/FeatureExtraction/otbComplexMomentImageFunction.txx
+++ b/Code/FeatureExtraction/otbComplexMomentImageFunction.txx
@@ -111,7 +111,9 @@ ComplexMomentImageFunction<TInput,TOutput,TCoordRep>
--q;
}
- Sum += ( ValP * ValQ * std::complex<float>(static_cast<float>(it.GetPixel(i)),0.0) );
+ Sum += ( ValP * ValQ * std::complex<float>(static_cast<float>(it.GetPixel(i)),0.0) );
+
+ //std::cout << Sum << std::endl;
}
return (static_cast<ComplexType>(Sum) );
diff --git a/Code/FeatureExtraction/otbHuImageFunction.txx b/Code/FeatureExtraction/otbHuImageFunction.txx
index 62b24cc4ab..d6e2feed25 100644
--- a/Code/FeatureExtraction/otbHuImageFunction.txx
+++ b/Code/FeatureExtraction/otbHuImageFunction.txx
@@ -62,18 +62,23 @@ HuImageFunction<TInput,TOutput,TCoordRep>
{
return ( itk::NumericTraits<RealType>::max() );
}
+
+
+/* std::cout << "Start" << this->GetStartIndex() << std::endl;
+ std::cout << "End" << this->GetEndIndex() << std::endl; */
if ( !this->IsInsideBuffer( index ) )
{
+ std::cout << index << std::endl;
return ( itk::NumericTraits<RealType>::max() );
}
assert(m_MomentNumber > 0);
assert(m_MomentNumber < 8);
-
+
function->SetInputImage( this->GetInputImage() );
//OTB-FA-00025-CS
- std::cout << "Neighbor " <<this->GetNeighborhoodRadius()<<std::endl;
+// std::cout << "Neighbor " <<this->GetNeighborhoodRadius()<<std::endl;
function->SetNeighborhoodRadius(this->GetNeighborhoodRadius() );
//OTB-FA-00024-CS
diff --git a/Examples/Segmentation/CMakeLists.txt b/Examples/Segmentation/CMakeLists.txt
index 087e2e1ec4..535beedcbc 100644
--- a/Examples/Segmentation/CMakeLists.txt
+++ b/Examples/Segmentation/CMakeLists.txt
@@ -8,11 +8,19 @@ INCLUDE_REGULAR_EXPRESSION("^.*$")
ADD_EXECUTABLE(ConnectedThresholdImageFilter ConnectedThresholdImageFilter.cxx )
TARGET_LINK_LIBRARIES(ConnectedThresholdImageFilter OTBCommon OTBIO ITKNumerics ITKIO)
+ADD_EXECUTABLE(OtsuThresholdImageFilter OtsuThresholdImageFilter.cxx )
+TARGET_LINK_LIBRARIES(OtsuThresholdImageFilter OTBCommon OTBIO ITKCommon ITKIO)
+
+ADD_EXECUTABLE(OtsuMultipleThresholdImageFilter OtsuMultipleThresholdImageFilter.cxx )
+TARGET_LINK_LIBRARIES(OtsuMultipleThresholdImageFilter
+ OTBCommon OTBIO ITKCommon ITKIO ITKStatistics)
+
#ADD_EXECUTABLE(ConfidenceConnected ConfidenceConnected.cxx )
#TARGET_LINK_LIBRARIES(ConfidenceConnected ITKNumerics ITKIO)
-#ADD_EXECUTABLE(NeighborhoodConnectedImageFilter NeighborhoodConnectedImageFilter.cxx )
-#TARGET_LINK_LIBRARIES(NeighborhoodConnectedImageFilter ITKNumerics ITKIO)
+ADD_EXECUTABLE(NeighborhoodConnectedImageFilter NeighborhoodConnectedImageFilter.cxx )
+TARGET_LINK_LIBRARIES(NeighborhoodConnectedImageFilter OTBCommon OTBIO
+ITKNumerics ITKIO)
#ADD_EXECUTABLE(IsolatedConnectedImageFilter IsolatedConnectedImageFilter.cxx )
#TARGET_LINK_LIBRARIES(IsolatedConnectedImageFilter ITKNumerics ITKIO)
diff --git a/Examples/Segmentation/NeighborhoodConnectedImageFilter.cxx b/Examples/Segmentation/NeighborhoodConnectedImageFilter.cxx
new file mode 100644
index 0000000000..781a2b6c8e
--- /dev/null
+++ b/Examples/Segmentation/NeighborhoodConnectedImageFilter.cxx
@@ -0,0 +1,342 @@
+
+#if defined(_MSC_VER)
+#pragma warning ( disable : 4786 )
+#endif
+
+#ifdef __BORLANDC__
+#define ITK_LEAN_AND_MEAN
+#endif
+
+// Software Guide : BeginCommandLineArgs
+// INPUTS: {QB_Suburb.png}
+// OUTPUTS: {NeighborhoodConnectedThresholdOutput1.png}
+// 110 38 50 100
+// Software Guide : EndCommandLineArgs
+// Software Guide : BeginCommandLineArgs
+// INPUTS: {QB_Suburb.png}
+// OUTPUTS: {NeighborhoodConnectedThresholdOutput2.png}
+// 118 100 0 10
+// Software Guide : EndCommandLineArgs
+// Software Guide : BeginCommandLineArgs
+// INPUTS: {QB_Suburb.png}
+// OUTPUTS: {NeighborhoodConnectedThresholdOutput3.png}
+// 169 146 220 255
+// Software Guide : EndCommandLineArgs
+
+// Software Guide : BeginLatex
+//
+// The following example illustrates the use of the
+// \doxygen{itk::NeighborhoodConnectedImageFilter}. This filter is a close variant
+// of the \doxygen{itk::ConnectedThresholdImageFilter}. On one hand, the
+// ConnectedThresholdImageFilter accepts a pixel in the region if its intensity
+// is in the interval defined by two user-provided threshold values. The
+// NeighborhoodConnectedImageFilter, on the other hand, will only accept a
+// pixel if \textbf{all} its neighbors have intensities that fit in the
+// interval. The size of the neighborhood to be considered around each pixel is
+// defined by a user-provided integer radius.
+//
+// The reason for considering the neighborhood intensities instead of only the
+// current pixel intensity is that small structures are less likely to be
+// accepted in the region. The operation of this filter is equivalent to
+// applying the ConnectedThresholdImageFilter followed by mathematical
+// morphology erosion using a structuring element of the same shape as
+// the neighborhood provided to the NeighborhoodConnectedImageFilter.
+//
+// Software Guide : EndLatex
+
+
+// Software Guide : BeginCodeSnippet
+#include "itkNeighborhoodConnectedImageFilter.h"
+// Software Guide : EndCodeSnippet
+
+
+#include "otbImage.h"
+#include "itkCastImageFilter.h"
+
+
+// Software Guide : BeginLatex
+//
+// The \doxygen{itk::CurvatureFlowImageFilter} is used here to smooth the image
+// while preserving edges.
+//
+// Software Guide : EndLatex
+
+// Software Guide : BeginCodeSnippet
+#include "itkCurvatureFlowImageFilter.h"
+// Software Guide : EndCodeSnippet
+
+
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+
+
+int main( int argc, char *argv[] )
+{
+ if( argc < 7 )
+ {
+ std::cerr << "Missing Parameters " << std::endl;
+ std::cerr << "Usage: " << argv[0];
+ std::cerr << " inputImage outputImage seedX seedY lowerThreshold upperThreshold" << std::endl;
+ return 1;
+ }
+
+
+ // Software Guide : BeginLatex
+ //
+ // We now define the image type using a particular pixel type and image
+ // dimension. In this case the \code{float} type is used for the pixels due
+ // to the requirements of the smoothing filter.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef float InternalPixelType;
+ const unsigned int Dimension = 2;
+ typedef itk::Image< InternalPixelType, Dimension > InternalImageType;
+ // Software Guide : EndCodeSnippet
+
+ //FIXME : OTBIMAGE
+ typedef unsigned char OutputPixelType;
+ typedef itk::Image< OutputPixelType, Dimension > OutputImageType;
+
+ typedef itk::CastImageFilter< InternalImageType, OutputImageType >
+ CastingFilterType;
+ CastingFilterType::Pointer caster = CastingFilterType::New();
+
+
+ // We instantiate reader and writer types
+ //
+ typedef otb::ImageFileReader< InternalImageType > ReaderType;
+ typedef otb::ImageFileWriter< OutputImageType > WriterType;
+
+ ReaderType::Pointer reader = ReaderType::New();
+ WriterType::Pointer writer = WriterType::New();
+
+ reader->SetFileName( argv[1] );
+ writer->SetFileName( argv[2] );
+
+
+ // Software Guide : BeginLatex
+ //
+ // The smoothing filter type is instantiated using the image type as
+ // a template parameter.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::CurvatureFlowImageFilter<InternalImageType, InternalImageType>
+ CurvatureFlowImageFilterType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // Then, the filter is created by invoking the \code{New()} method and
+ // assigning the result to a \doxygen{itk::SmartPointer}.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ CurvatureFlowImageFilterType::Pointer smoothing =
+ CurvatureFlowImageFilterType::New();
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // We now declare the type of the region growing filter. In this case it is
+ // the NeighborhoodConnectedImageFilter.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::NeighborhoodConnectedImageFilter<InternalImageType,
+ InternalImageType > ConnectedFilterType;
+ // Software Guide : EndCodeSnippet
+
+ // Software Guide : BeginLatex
+ //
+ // One filter of this class is constructed using the \code{New()} method.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ ConnectedFilterType::Pointer neighborhoodConnected = ConnectedFilterType::New();
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // Now it is time to create a simple, linear data processing pipeline. A
+ // file reader is added at the beginning of the pipeline and a cast
+ // filter and writer are added at the end. The cast filter is required
+ // to convert \code{float} pixel types to integer types since only a
+ // few image file formats support \code{float} types.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ smoothing->SetInput( reader->GetOutput() );
+ neighborhoodConnected->SetInput( smoothing->GetOutput() );
+ caster->SetInput( neighborhoodConnected->GetOutput() );
+ writer->SetInput( caster->GetOutput() );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The CurvatureFlowImageFilter requires a couple of parameters to
+ // be defined. The following are typical values for $2D$ images. However
+ // they may have to be adjusted depending on the amount of noise present in
+ // the input image.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ smoothing->SetNumberOfIterations( 5 );
+ smoothing->SetTimeStep( 0.125 );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The NeighborhoodConnectedImageFilter requires that two main parameters
+ // are specified. They are the lower and upper thresholds of the interval
+ // in which intensity values must fall to be included in the
+ // region. Setting these two values too close will not allow enough
+ // flexibility for the region to grow. Setting them too far apart will
+ // result in a region that engulfs the image.
+ //
+ // \index{itk::NeighborhoodConnectedImageFilter!SetLower()}
+ // \index{itk::NeighborhoodConnectedImageFilter!SetUppder()}
+ //
+ // Software Guide : EndLatex
+
+ const InternalPixelType lowerThreshold = atof( argv[5] );
+ const InternalPixelType upperThreshold = atof( argv[6] );
+
+ // Software Guide : BeginCodeSnippet
+ neighborhoodConnected->SetLower( lowerThreshold );
+ neighborhoodConnected->SetUpper( upperThreshold );
+ // Software Guide : EndCodeSnippet
+
+ // Software Guide : BeginLatex
+ //
+ // Here, we add the crucial parameter that defines the neighborhood size
+ // used to determine whether a pixel lies in the region. The larger the
+ // neighborhood, the more stable this filter will be against noise in the
+ // input image, but also the longer the computing time will be. Here we
+ // select a filter of radius $2$ along each dimension. This results in a
+ // neighborhood of $5 \times 5$ pixels.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ InternalImageType::SizeType radius;
+
+ radius[0] = 2; // two pixels along X
+ radius[1] = 2; // two pixels along Y
+
+ neighborhoodConnected->SetRadius( radius );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // As in the ConnectedThresholdImageFilter we must now provide the
+ // intensity value to be used for the output pixels accepted in the region
+ // and at least one seed point to define the initial region.
+ //
+ // \index{itk::NeighborhoodConnectedImageFilter!SetSeed()}
+ // \index{itk::NeighborhoodConnectedImageFilter!SetReplaceValue()}
+ //
+ // Software Guide : EndLatex
+
+ InternalImageType::IndexType index;
+
+ index[0] = atoi( argv[3] );
+ index[1] = atoi( argv[4] );
+
+
+ // Software Guide : BeginCodeSnippet
+ neighborhoodConnected->SetSeed( index );
+ neighborhoodConnected->SetReplaceValue( 255 );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The invocation of the \code{Update()} method on the writer triggers the
+ // execution of the pipeline. It is usually wise to put update calls in a
+ // \code{try/catch} block in case errors occur and exceptions are thrown.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ try
+ {
+ writer->Update();
+ }
+ catch( itk::ExceptionObject & excep )
+ {
+ std::cerr << "Exception caught !" << std::endl;
+ std::cerr << excep << std::endl;
+ }
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // Let's run this example using as input the image
+ // \code{QB\_Suburb.png} provided in the directory
+ // \code{Examples/Data}. We can easily segment the major
+ // structures by providing seeds in the appropriate locations and defining
+ // values for the lower and upper thresholds.
+ // Figure~\ref{fig:NeighborhoodConnectedThresholdOutput} illustrates several examples of
+ // segmentation. The parameters used are presented in
+ // Table~\ref{tab:NeighborhoodConnectedThresholdOutput}.
+ //
+ // \begin{table}
+ // \begin{center}
+ // \begin{tabular}{|l|c|c|c|c|}
+ // \hline
+ // Structure & Seed Index & Lower & Upper & Output Image \\ \hline
+ // Road & $(110,38)$ & 50 & 100 & Second from left in Figure \ref{fig:NeighborhoodConnectedThresholdOutput} \\ \hline
+ // Shadow & $(118,100)$ & 0 & 10 & Third from left in Figure \ref{fig:NeighborhoodConnectedThresholdOutput} \\ \hline
+ // Building & $(169,146)$ & 220 & 255 & Fourth from left in Figure \ref{fig:NeighborhoodConnectedThresholdOutput} \\ \hline
+ // \end{tabular}
+ // \end{center}
+ // \itkcaption[NeighborhoodConnectedThreshold example parameters]{Parameters used for
+ // segmenting some structures shown in
+ // Figure~\ref{fig:NeighborhoodConnectedThresholdOutput} with the filter
+ // \doxygen{itk::NeighborhoodConnectedThresholdImageFilter}.\label{tab:NeighborhoodConnectedThresholdOutput}}
+ // \end{table}
+ //
+ // \begin{figure} \center
+ // \includegraphics[width=0.24\textwidth]{QB_Suburb.eps}
+ // \includegraphics[width=0.24\textwidth]{NeighborhoodConnectedThresholdOutput1.eps}
+ // \includegraphics[width=0.24\textwidth]{NeighborhoodConnectedThresholdOutput2.eps}
+ // \includegraphics[width=0.24\textwidth]{NeighborhoodConnectedThresholdOutput3.eps}
+ // \itkcaption[NeighborhoodConnectedThreshold segmentation results]{Segmentation results
+ // for the NeighborhoodConnectedThreshold filter for various seed points.}
+ // \label{fig:NeighborhoodConnectedThresholdOutput}
+ // \end{figure}
+ //
+ // As with the ConnectedThresholdImageFilter, several seeds could
+ // be provided to the filter by using the \code{AddSeed()} method.
+ // Compare the output of Figure
+ // \ref{fig:NeighborhoodConnectedImageFilterOutput} with those of Figure
+ // \ref{fig:ConnectedThresholdOutput} produced by the
+ // ConnectedThresholdImageFilter. You may want to play with the
+ // value of the neighborhood radius and see how it affect the smoothness of
+ // the segmented object borders, the size of the segmented region and how
+ // much that costs in computing time.
+ //
+ // Software Guide : EndLatex
+
+ return 0;
+}
+
+
+
+
diff --git a/Examples/Segmentation/OtsuMultipleThresholdImageFilter.cxx b/Examples/Segmentation/OtsuMultipleThresholdImageFilter.cxx
new file mode 100755
index 0000000000..c347ea383c
--- /dev/null
+++ b/Examples/Segmentation/OtsuMultipleThresholdImageFilter.cxx
@@ -0,0 +1,195 @@
+
+#if defined(_MSC_VER)
+#pragma warning ( disable : 4786 )
+#endif
+
+#ifdef __BORLANDC__
+#define ITK_LEAN_AND_MEAN
+#endif
+
+// Software Guide : BeginCommandLineArgs
+// INPUTS: {QB_Suburb.png}
+// OUTPUTS: {OtsuMultipleThresholdsOutput000.png},{OtsuMultipleThresholdsOutput001.png}, {OtsuMultipleThresholdsOutput002.png}
+// Software Guide : EndCommandLineArgs
+
+// Software Guide : BeginLatex
+// This example illustrates how to use the \doxygen{itk::OtsuMultipleThresholdsCalculator}.
+// Software Guide : EndLatex
+
+// Software Guide : BeginCodeSnippet
+#include "itkOtsuMultipleThresholdsCalculator.h"
+// Software Guide : EndCodeSnippet
+
+#include "otbImage.h"
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+#include "itkScalarImageToHistogramGenerator.h"
+#include "itkBinaryThresholdImageFilter.h"
+#include "itkNumericTraits.h"
+
+#include <stdio.h>
+int main( int argc, char * argv[] )
+{
+ if( argc < 2 )
+ {
+ std::cerr << "Usage: " << argv[0];
+ std::cerr << " inputImageFile outputImageFileName1 [OutputImageFilename2 ...] ";
+ return EXIT_FAILURE;
+ }
+
+ //Convenience typedefs
+ typedef unsigned char InputPixelType;
+ typedef unsigned char OutputPixelType;
+
+ typedef otb::Image< InputPixelType, 2 > InputImageType;
+ typedef otb::Image< OutputPixelType, 2 > OutputImageType;
+
+ // Software Guide : BeginLatex
+ // OtsuMultipleThresholdsCalculator calculates thresholds for a give histogram
+ // so as to maximize the between-class variance. We use
+ // ScalarImageToHistogramGenerator to generate histograms
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::Statistics::ScalarImageToHistogramGenerator< InputImageType >
+ ScalarImageToHistogramGeneratorType;
+ typedef itk::OtsuMultipleThresholdsCalculator<
+ ScalarImageToHistogramGeneratorType::HistogramType > CalculatorType;
+ // Software Guide : EndCodeSnippet
+
+ typedef otb::ImageFileReader< InputImageType > ReaderType;
+ typedef otb::ImageFileWriter< InputImageType > WriterType;
+
+ // Software Guide : BeginLatex
+ // Once thresholds are computed we will use BinaryThresholdImageFilter to
+ // segment the input image into segments.
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::BinaryThresholdImageFilter< InputImageType, OutputImageType >
+ FilterType;
+ // Software Guide : EndCodeSnippet
+
+ //Create using static New() method
+
+ // Software Guide : BeginCodeSnippet
+ ScalarImageToHistogramGeneratorType::Pointer scalarImageToHistogramGenerator =
+ ScalarImageToHistogramGeneratorType::New();
+ CalculatorType::Pointer calculator = CalculatorType::New();
+ FilterType::Pointer filter = FilterType::New();
+ // Software Guide : EndCodeSnippet
+
+ ReaderType::Pointer reader = ReaderType::New();
+ WriterType::Pointer writer = WriterType::New();
+
+ //Set Properties
+
+ // Software Guide : BeginCodeSnippet
+ scalarImageToHistogramGenerator->SetNumberOfBins(128);
+ int nbThresholds = argc-2;
+ calculator->SetNumberOfThresholds( nbThresholds );
+ // Software Guide : EndCodeSnippet
+
+ const OutputPixelType outsideValue = 0;
+ const OutputPixelType insideValue = 255;
+ filter->SetOutsideValue( outsideValue );
+ filter->SetInsideValue( insideValue );
+
+ //Connect Pipeline
+ reader->SetFileName( argv[1] );
+
+ // Software Guide : BeginLatex
+ // The pipeline will look as follows:
+ // Software Guide : EndLatex
+ // Software Guide : BeginCodeSnippet
+ scalarImageToHistogramGenerator->SetInput(reader->GetOutput());
+ calculator->SetInputHistogram(scalarImageToHistogramGenerator->GetOutput());
+ filter->SetInput( reader->GetOutput() );
+ writer->SetInput(filter->GetOutput());
+ // Software Guide : EndCodeSnippet
+
+
+ //Invoke pipeline
+ try
+ { reader->Update(); }
+ catch( itk::ExceptionObject & excp )
+ {
+ std::cerr << "Exception thrown while reading image" << excp << std::endl;
+ }
+ scalarImageToHistogramGenerator->Compute();
+
+ try
+ { calculator->Update(); }
+ catch( itk::ExceptionObject & excp )
+ {
+ std::cerr << "Exception thrown " << excp << std::endl;
+ }
+
+ // Software Guide : BeginLatex
+ // Thresholds are obtained using the \code{GetOutput} method
+ // \index{itk::OtsuMultipleThresholdsCalculator!GetOutput()}
+ // Software Guide : EndLatex
+ //Get Thresholds
+ // Software Guide : BeginCodeSnippet
+ const CalculatorType::OutputType &thresholdVector = calculator->GetOutput();
+ CalculatorType::OutputType::const_iterator itNum = thresholdVector.begin();
+ // Software Guide : EndCodeSnippet
+
+ //Threshold into seperate segments and write out as binary images
+ double lowerThreshold = 0;
+ double upperThreshold;
+
+ unsigned int counter = 0;
+ // Software Guide : BeginCodeSnippet
+ for(; itNum < thresholdVector.end(); itNum++)
+ {
+ std::cout << "OtsuThreshold["
+ << (int)(itNum - thresholdVector.begin())
+ << "] = " <<
+ static_cast<itk::NumericTraits<CalculatorType::MeasurementType>::PrintType>
+ (*itNum) << std::endl;
+ // Software Guide : EndCodeSnippet
+
+ upperThreshold = (*itNum);
+ filter->SetLowerThreshold( static_cast<OutputPixelType> (lowerThreshold) );
+ filter->SetUpperThreshold( static_cast<OutputPixelType> (upperThreshold) );
+ lowerThreshold = upperThreshold;
+
+
+ writer->SetFileName( argv[2+counter] );
+ ++counter;
+ try
+ { writer->Update(); }
+ catch( itk::ExceptionObject & excp )
+ {
+ std::cerr << "Exception thrown " << excp << std::endl;
+ }
+ // Software Guide : BeginCodeSnippet
+ }
+ // Software Guide : EndCodeSnippet
+
+ // Software Guide : BeginLatex
+ //
+ // \begin{figure}
+ // \center
+ // \includegraphics[width=0.44\textwidth]{QB_Suburb.eps}
+ // \includegraphics[width=0.44\textwidth]{OtsuMultipleThresholdsOutput000.eps}
+ // \includegraphics[width=0.44\textwidth]{OtsuMultipleThresholdsOutput001.eps}
+ // \includegraphics[width=0.44\textwidth]{OtsuMultipleThresholdsOutput002.eps}
+ // \itkcaption[OtsuThresholdImageFilter output]{Effect of the OtsuMultipleThresholdImageFilter.}
+ // \label{fig:OtsuMultipleThresholdImageFilterInputOutput}
+ // \end{figure}
+ //
+ // Figure \ref{fig:OtsuMultipleThresholdImageFilterInputOutput} illustrates the
+ // effect of this filter.
+ //
+ // \relatedClasses
+ // \begin{itemize}
+ // \item \doxygen{itk::ThresholdImageFilter}
+ // \end{itemize}
+ //
+ // Software Guide : EndLatex
+
+ return EXIT_SUCCESS;
+}
+
diff --git a/Examples/Segmentation/OtsuThresholdImageFilter.cxx b/Examples/Segmentation/OtsuThresholdImageFilter.cxx
new file mode 100755
index 0000000000..7081963931
--- /dev/null
+++ b/Examples/Segmentation/OtsuThresholdImageFilter.cxx
@@ -0,0 +1,231 @@
+#if defined(_MSC_VER)
+#pragma warning ( disable : 4786 )
+#endif
+
+#ifdef __BORLANDC__
+#define ITK_LEAN_AND_MEAN
+#endif
+
+// Software Guide : BeginCommandLineArgs
+// INPUTS: {QB_Suburb.png}
+// OUTPUTS: {OtsuThresholdImageFilterOutput.png}
+// 255 0
+// Software Guide : EndCommandLineArgs
+
+// Software Guide : BeginLatex
+//
+// This example illustrates how to use the \doxygen{itk::OtsuThresholdImageFilter}.
+//
+// Software Guide : EndLatex
+
+// Software Guide : BeginCodeSnippet
+#include "itkOtsuThresholdImageFilter.h"
+// Software Guide : EndCodeSnippet
+
+#include "otbImage.h"
+#include "otbImageFileReader.h"
+#include "otbImageFileWriter.h"
+
+int main( int argc, char * argv[] )
+{
+ if( argc < 5 )
+ {
+ std::cerr << "Usage: " << argv[0];
+ std::cerr << " inputImageFile outputImageFile ";
+ std::cerr << " insideValue outsideValue " << std::endl;
+ return EXIT_FAILURE;
+ }
+
+ // Software Guide : BeginLatex
+ //
+ // The next step is to decide which pixel types to use for the input and output
+ // images.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef unsigned char InputPixelType;
+ typedef unsigned char OutputPixelType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The input and output image types are now defined using their respective
+ // pixel types and dimensions.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::Image< InputPixelType, 2 > InputImageType;
+ typedef itk::Image< OutputPixelType, 2 > OutputImageType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The filter type can be instantiated using the input and output image
+ // types defined above.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef itk::OtsuThresholdImageFilter<
+ InputImageType, OutputImageType > FilterType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // An \doxygen{otb::ImageFileReader} class is also instantiated in order to read
+ // image data from a file. (See Section \ref{sec:IO} on page
+ // \pageref{sec:IO} for more information about reading
+ // and writing data.)
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ typedef otb::ImageFileReader< InputImageType > ReaderType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // An \doxygen{otb::ImageFileWriter} is instantiated in order to write the output
+ // image to a file.
+ //
+ // Software Guide : EndLatex
+
+
+ // Software Guide : BeginCodeSnippet
+ typedef otb::ImageFileWriter< InputImageType > WriterType;
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // Both the filter and the reader are created by invoking their \code{New()}
+ // methods and assigning the result to \doxygen{SmartPointer}s.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ ReaderType::Pointer reader = ReaderType::New();
+ FilterType::Pointer filter = FilterType::New();
+ // Software Guide : EndCodeSnippet
+
+ WriterType::Pointer writer = WriterType::New();
+ writer->SetInput( filter->GetOutput() );
+ reader->SetFileName( argv[1] );
+
+
+ // Software Guide : BeginLatex
+ //
+ // The image obtained with the reader is passed as input to the
+ // OtsuThresholdImageFilter.
+ //
+ // \index{itk::Otsu\-Threshold\-Image\-Filter!SetInput()}
+ // \index{otb::FileImageReader!GetOutput()}
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ filter->SetInput( reader->GetOutput() );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The method \code{SetOutsideValue()} defines the intensity value to be
+ // assigned to those pixels whose intensities are outside the range defined
+ // by the lower and upper thresholds. The method \code{SetInsideValue()}
+ // defines the intensity value to be assigned to pixels with intensities
+ // falling inside the threshold range.
+ //
+ // \index{itk::Otsu\-Threshold\-Image\-Filter!SetOutsideValue()}
+ // \index{itk::Otsu\-Threshold\-Image\-Filter!SetInsideValue()}
+ // \index{SetOutsideValue()!itk::Otsu\-Threshold\-Image\-Filter}
+ // \index{SetInsideValue()!itk::Otsu\-Threshold\-Image\-Filter}
+ //
+ // Software Guide : EndLatex
+
+ const OutputPixelType outsideValue = atoi( argv[3] );
+ const OutputPixelType insideValue = atoi( argv[4] );
+
+ // Software Guide : BeginCodeSnippet
+ filter->SetOutsideValue( outsideValue );
+ filter->SetInsideValue( insideValue );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The method \code{SetNumberOfHistogramBins()} defines the number of bins
+ // to be used for computing the histogram. This histogram will be used
+ // internally in order to compute the Otsu threshold.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ filter->SetNumberOfHistogramBins( 128 );
+ // Software Guide : EndCodeSnippet
+
+
+ // Software Guide : BeginLatex
+ //
+ // The execution of the filter is triggered by invoking the \code{Update()}
+ // method. If the filter's output has been passed as input to subsequent
+ // filters, the \code{Update()} call on any posterior filters in the
+ // pipeline will indirectly trigger the update of this filter.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ filter->Update();
+ // Software Guide : EndCodeSnippet
+
+
+
+ // Software Guide : BeginLatex
+ //
+ // We print out here the Threshold value that was computed internally by the
+ // filter. For this we invoke the \code{GetThreshold} method.
+ //
+ // Software Guide : EndLatex
+
+ // Software Guide : BeginCodeSnippet
+ int threshold = filter->GetThreshold();
+ std::cout << "Threshold = " << threshold << std::endl;
+ // Software Guide : EndCodeSnippet
+
+
+
+ // Software Guide : BeginLatex
+ //
+ // \begin{figure}
+ // \center
+ // \includegraphics[width=0.44\textwidth]{QB_Suburb.eps}
+ // \includegraphics[width=0.44\textwidth]{OtsuThresholdImageFilterOutput.eps}
+ // \itkcaption[OtsuThresholdImageFilter output]{Effect of the OtsuThresholdImageFilter.}
+ // \label{fig:OtsuThresholdImageFilterInputOutput}
+ // \end{figure}
+ //
+ // Figure \ref{fig:OtsuThresholdImageFilterInputOutput} illustrates the
+ // effect of this filter. This
+ // figure shows the limitations of this filter for performing segmentation
+ // by itself. These limitations are particularly noticeable in noisy images
+ // and in images lacking spatial uniformity.
+ //
+ // \relatedClasses
+ // \begin{itemize}
+ // \item \doxygen{itk::ThresholdImageFilter}
+ // \end{itemize}
+ //
+ // Software Guide : EndLatex
+
+ writer->SetFileName( argv[2] );
+ writer->Update();
+
+ return EXIT_SUCCESS;
+}
+
--
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