ITK/Examples/ImageSegmentation/ExtractContourWithSnakes: Difference between revisions
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This is my ITK implementation of Snakes by following the [http://www.cb.uu.se/~cris/ Cris Luengo] Matlab [http://www.cb.uu.se/~cris/blog/index.php/archives/217/comment-page-1 tutorial]. | This is my ITK implementation of Snakes by following the [http://www.cb.uu.se/~cris/ Cris Luengo] Matlab [http://www.cb.uu.se/~cris/blog/index.php/archives/217/comment-page-1 tutorial]. | ||
Invoke using '''./ | Invoke using '''./ExtractContourWithSnakesSnakes 100 0.01 0.4 0.07 4 6000''' | ||
[[File:Snakes.png]] | [[File:Snakes.png]] | ||
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#include "itkGradientMagnitudeImageFilter.h" | #include "itkGradientMagnitudeImageFilter.h" | ||
#include "itkImageFileReader.h" | #include "itkImageFileReader.h" | ||
#include <vnl/vnl_matrix.h> | #include <vnl/vnl_matrix.h> | ||
#include "vnl/algo/vnl_determinant.h" | #include "vnl/algo/vnl_determinant.h" | ||
#include "vnl/algo/vnl_matrix_inverse.h" | #include "vnl/algo/vnl_matrix_inverse.h" | ||
#include <vnl/vnl_vector.h> | #include <vnl/vnl_vector.h> | ||
#include <iostream> | #include <iostream> | ||
typedef itk::Image< unsigned char, 2 > | typedef itk::Image< unsigned char, 2 > ImageType; | ||
typedef itk::Image< float, 2 > | typedef itk::Image< float, 2 > FloatImageType; | ||
typedef ImageType::IndexType IndexType; | typedef ImageType::IndexType IndexType; | ||
typedef itk::CovariantVector< float, 2 > | typedef itk::CovariantVector< float, 2 > OutputPixelType; | ||
typedef itk::Image< OutputPixelType, 2 > | typedef itk::Image< OutputPixelType, 2 > OutputImageType; | ||
typedef itk::GradientRecursiveGaussianImageFilter<FloatImageType, OutputImageType> FilterType; | typedef itk::GradientRecursiveGaussianImageFilter< | ||
typedef itk::GradientMagnitudeImageFilter<ImageType, FloatImageType > | FloatImageType, OutputImageType> FilterType; | ||
typedef itk::ImageFileReader< ImageType > | typedef itk::GradientMagnitudeImageFilter< | ||
ImageType, FloatImageType > GradMagfilterType; | |||
vnl_vector<double> generateCircle(double cx, double cy, double rx, double ry, int n); | typedef itk::ImageFileReader< ImageType > ReaderType; | ||
void createImage(ImageType::Pointer image, int w, int h, double cx, double cy, double rx, double ry); | |||
vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int); | vnl_vector<double> generateCircle(double cx, double cy, | ||
vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position); | double rx, double ry, int n); | ||
void createImage(ImageType::Pointer image, | |||
int w, int h, double cx, double cy, double rx, double ry); | |||
vnl_matrix<double> computeP(double alpha, double beta, double gamma, | |||
double N) throw (int); | |||
vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, | |||
OutputImageType::Pointer gradient, | |||
int position); | |||
int main( int argc, char* argv[] ) | int main( int argc, char* argv[] ) | ||
{ | { | ||
//Image dimensions | |||
int w = 300; | |||
int h = 300; | |||
ImageType::Pointer image; | |||
if (argc < 7) | |||
{ | |||
std::cout << "Usage " << argv[0] | |||
<< " points alpha beta gamma sigma iterations [image]" | |||
<< std::endl; | |||
return EXIT_SUCCESS;; | |||
} | |||
else if (argc < 8) | |||
{ | |||
//Synthesize the image | |||
image = ImageType::New(); | |||
createImage(image, w, h, 150, 150, 50, 50); | |||
} | |||
else if (argc == 8) | |||
{ | |||
//Open the image | |||
ReaderType::Pointer reader = ReaderType::New(); | |||
reader->SetFileName( argv[7] ); | |||
try | |||
{ | |||
reader->Update(); | |||
image = reader->GetOutput(); | |||
w = image->GetLargestPossibleRegion().GetSize()[0]; | |||
h = image->GetLargestPossibleRegion().GetSize()[1]; | |||
} | |||
catch( itk::ExceptionObject & err ) | |||
{ | |||
std::cerr << "Caught unexpected exception " << err; | |||
return EXIT_FAILURE; | |||
} | |||
} | |||
//Snake parameters | |||
double alpha = 0.001; | |||
double beta = 0.4; | |||
double gamma = 100; | |||
double iterations = 1; | |||
int nPoints = 20; | |||
double sigma; | |||
nPoints = atoi(argv[1]); | |||
alpha = atof(argv[2]); | |||
beta = atof(argv[3]); | |||
gamma = atof(argv[4]); | |||
sigma = atof(argv[5]); | |||
iterations = atoi(argv[6]); | |||
//Temporal variables | |||
vnl_matrix<double> P; | |||
vnl_vector<double> v; | |||
double N; | |||
//Generate initial snake circle | |||
v = generateCircle(130, 130, 50, 50, nPoints); | |||
//Computes P matrix. | |||
N = v.size()/2; | |||
try | |||
{ | |||
P = computeP(alpha, beta, gamma, N); | |||
} | |||
catch (int n) | |||
{ | |||
return EXIT_FAILURE;; | |||
} | |||
//Computes the magnitude gradient | |||
GradMagfilterType::Pointer gradientMagnitudeFilter = | |||
GradMagfilterType::New(); | |||
gradientMagnitudeFilter->SetInput( image ); | |||
gradientMagnitudeFilter->Update(); | |||
//Computes the gradient of the gradient magnitude | |||
FilterType::Pointer gradientFilter = FilterType::New(); | |||
gradientFilter->SetInput( gradientMagnitudeFilter->GetOutput() ); | |||
gradientFilter->SetSigma( sigma ); | |||
gradientFilter->Update(); | |||
//Loop | |||
vnl_vector<double> x(N); | |||
vnl_vector<double> y(N); | |||
std::cout << "Initial snake" << std::endl; | |||
for (int i = 0; i < N; i++) | |||
{ | |||
x[i] = v[2*i]; | |||
y[i] = v[2*i+1]; | |||
std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; | |||
} | |||
for (int i = 0; i < iterations; i++) | |||
{ | |||
vnl_vector<double> fex; | |||
vnl_vector<double> fey; | |||
fex = sampleImage(x, y, gradientFilter->GetOutput(), 0); | |||
fey = sampleImage(x, y, gradientFilter->GetOutput(), 1); | |||
x = (x+gamma*fex).post_multiply(P); | |||
y = (y+gamma*fey).post_multiply(P); | |||
} | |||
//Display the answer | |||
std::cout << "Final snake after " << iterations << " iterations" << std::endl; | |||
vnl_vector<double> v2(2*N); | |||
for (int i=0; i<N; i++) | |||
{ | |||
v2[2*i] = x[i]; | |||
v2[2*i+1] = y[i]; | |||
std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; | |||
} | |||
return EXIT_SUCCESS;; | |||
} | } | ||
vnl_vector<double> generateCircle(double cx, double cy, double rx, double ry, int n) { | vnl_vector<double> generateCircle( | ||
double cx, double cy, double rx, double ry, int n) | |||
{ | |||
vnl_vector<double> v(2*(n+1)); | |||
for (int i=0; i<n; i++) | |||
{ | |||
v[2*i] = cx + rx*cos(2*M_PI*i/n); | |||
v[2*i+1] = cy + ry*sin(2*M_PI*i/n); | |||
} | |||
v[2*n]=v[0]; | |||
v[2*n+1]=v[1]; | |||
return v; | |||
} | } | ||
void createImage(ImageType::Pointer image, int w, int h, double cx, double cy, double rx, double ry) { | void createImage(ImageType::Pointer image, | ||
int w, int h, double cx, double cy, double rx, double ry) | |||
{ | |||
itk::Size<2> size; | |||
size[0] = w; | |||
size[1] = h; | |||
itk::RandomImageSource<ImageType>::Pointer randomImageSource = itk::RandomImageSource<ImageType>::New(); | |||
randomImageSource->SetNumberOfThreads(1); // to produce non-random results | |||
randomImageSource->SetSize(size); | |||
randomImageSource->SetMin(200); | |||
randomImageSource->SetMax(255); | |||
randomImageSource->Update(); | |||
image->SetRegions(randomImageSource->GetOutput()->GetLargestPossibleRegion()); | |||
image->Allocate(); | |||
IndexType index; | |||
//Draw oval. | |||
for (int i=0; i<w; i++) | |||
{ | |||
for (int j=0; j<h; j++) | |||
{ | |||
index[0] = i; index[1] = j; | |||
if ( ((i-cx)*(i-cx)/(rx*rx) + (j-cy)*(j-cy)/(ry*ry) ) < 1) | |||
{ | |||
image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)-100); | |||
} | |||
else | |||
{ | |||
image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)); | |||
} | |||
} | |||
} | |||
} | } | ||
vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int) { | vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int) | ||
{ | |||
double a = gamma*(2*alpha+6*beta)+1; | |||
double b = gamma*(-alpha-4*beta); | |||
double c = gamma*beta; | |||
vnl_matrix<double> P(N,N); | |||
P.fill(0); | |||
//fill diagonal | |||
P.fill_diagonal(a); | |||
//fill next two diagonals | |||
for (int i=0; i<(N-1); i++) | |||
{ | |||
P(i+1,i) = b; | |||
P(i,i+1) = b; | |||
} | |||
//Moreover | |||
P(0, N-1)=b; | |||
P(N-1, 0)=b; | |||
//fill next two diagonals | |||
for (int i=0; i<(N-2); i++) | |||
{ | |||
P(i+2,i) = c; | |||
P(i,i+2) = c; | |||
} | |||
//Moreover | |||
P(0, N-2)=c; | |||
P(1, N-1)=c; | |||
P(N-2, 0)=c; | |||
P(N-1, 1)=c; | |||
if ( vnl_determinant(P) == 0.0 ) | |||
{ | |||
std::cerr << "Singular matrix. Determinant is 0." << std::endl; | |||
throw 2; | |||
} | |||
//Compute the inverse of the matrix P | |||
vnl_matrix< double > Pinv; | |||
Pinv = vnl_matrix_inverse< double >(P); | |||
return Pinv; | |||
} | } | ||
vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position) { | vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position) | ||
{ | |||
int size; | |||
size = x.size(); | |||
vnl_vector<double> ans(size); | |||
IndexType index; | |||
for (int i=0; i<size; i++) | |||
{ | |||
index[0] = x[i]; | |||
index[1] = y[i]; | |||
ans[i] = gradient->GetPixel(index)[position]; | |||
} | |||
return ans; | |||
} | } | ||
</source> | </source> | ||
{{ITKCMakeLists|{{SUBPAGENAME}}}} | {{ITKCMakeLists|{{SUBPAGENAME}}}} |
Revision as of 20:49, 11 July 2013
Introduction
This is my ITK implementation of Snakes by following the Cris Luengo Matlab tutorial.
Invoke using ./ExtractContourWithSnakesSnakes 100 0.01 0.4 0.07 4 6000
ExtractContourWithSnakes.cxx
<source lang="cpp">
- include "itkImage.h"
- include "itkRandomImageSource.h"
- include "itkGradientRecursiveGaussianImageFilter.h"
- include "itkGradientMagnitudeImageFilter.h"
- include "itkImageFileReader.h"
- include <vnl/vnl_matrix.h>
- include "vnl/algo/vnl_determinant.h"
- include "vnl/algo/vnl_matrix_inverse.h"
- include <vnl/vnl_vector.h>
- include <iostream>
typedef itk::Image< unsigned char, 2 > ImageType; typedef itk::Image< float, 2 > FloatImageType; typedef ImageType::IndexType IndexType; typedef itk::CovariantVector< float, 2 > OutputPixelType; typedef itk::Image< OutputPixelType, 2 > OutputImageType; typedef itk::GradientRecursiveGaussianImageFilter<
FloatImageType, OutputImageType> FilterType;
typedef itk::GradientMagnitudeImageFilter<
ImageType, FloatImageType > GradMagfilterType;
typedef itk::ImageFileReader< ImageType > ReaderType;
vnl_vector<double> generateCircle(double cx, double cy,
double rx, double ry, int n);
void createImage(ImageType::Pointer image,
int w, int h, double cx, double cy, double rx, double ry);
vnl_matrix<double> computeP(double alpha, double beta, double gamma,
double N) throw (int);
vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y,
OutputImageType::Pointer gradient, int position);
int main( int argc, char* argv[] ) {
//Image dimensions int w = 300; int h = 300; ImageType::Pointer image; if (argc < 7) { std::cout << "Usage " << argv[0] << " points alpha beta gamma sigma iterations [image]" << std::endl; return EXIT_SUCCESS;; } else if (argc < 8) { //Synthesize the image image = ImageType::New(); createImage(image, w, h, 150, 150, 50, 50); } else if (argc == 8) { //Open the image ReaderType::Pointer reader = ReaderType::New(); reader->SetFileName( argv[7] ); try { reader->Update(); image = reader->GetOutput(); w = image->GetLargestPossibleRegion().GetSize()[0]; h = image->GetLargestPossibleRegion().GetSize()[1]; } catch( itk::ExceptionObject & err ) { std::cerr << "Caught unexpected exception " << err; return EXIT_FAILURE; } } //Snake parameters double alpha = 0.001; double beta = 0.4; double gamma = 100; double iterations = 1; int nPoints = 20; double sigma; nPoints = atoi(argv[1]); alpha = atof(argv[2]); beta = atof(argv[3]); gamma = atof(argv[4]); sigma = atof(argv[5]); iterations = atoi(argv[6]); //Temporal variables vnl_matrix<double> P; vnl_vector<double> v; double N; //Generate initial snake circle v = generateCircle(130, 130, 50, 50, nPoints);
//Computes P matrix. N = v.size()/2; try { P = computeP(alpha, beta, gamma, N); } catch (int n) { return EXIT_FAILURE;; } //Computes the magnitude gradient GradMagfilterType::Pointer gradientMagnitudeFilter = GradMagfilterType::New(); gradientMagnitudeFilter->SetInput( image ); gradientMagnitudeFilter->Update(); //Computes the gradient of the gradient magnitude FilterType::Pointer gradientFilter = FilterType::New(); gradientFilter->SetInput( gradientMagnitudeFilter->GetOutput() ); gradientFilter->SetSigma( sigma ); gradientFilter->Update(); //Loop vnl_vector<double> x(N); vnl_vector<double> y(N); std::cout << "Initial snake" << std::endl; for (int i = 0; i < N; i++) { x[i] = v[2*i]; y[i] = v[2*i+1]; std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; } for (int i = 0; i < iterations; i++) { vnl_vector<double> fex; vnl_vector<double> fey; fex = sampleImage(x, y, gradientFilter->GetOutput(), 0); fey = sampleImage(x, y, gradientFilter->GetOutput(), 1); x = (x+gamma*fex).post_multiply(P); y = (y+gamma*fey).post_multiply(P); } //Display the answer std::cout << "Final snake after " << iterations << " iterations" << std::endl; vnl_vector<double> v2(2*N); for (int i=0; i<N; i++) { v2[2*i] = x[i]; v2[2*i+1] = y[i]; std::cout << "(" << x[i] << ", " << y[i] << ")" << std::endl; } return EXIT_SUCCESS;;
}
vnl_vector<double> generateCircle(
double cx, double cy, double rx, double ry, int n)
{
vnl_vector<double> v(2*(n+1)); for (int i=0; i<n; i++) { v[2*i] = cx + rx*cos(2*M_PI*i/n); v[2*i+1] = cy + ry*sin(2*M_PI*i/n); } v[2*n]=v[0]; v[2*n+1]=v[1]; return v;
}
void createImage(ImageType::Pointer image,
int w, int h, double cx, double cy, double rx, double ry)
{
itk::Size<2> size; size[0] = w; size[1] = h; itk::RandomImageSource<ImageType>::Pointer randomImageSource = itk::RandomImageSource<ImageType>::New(); randomImageSource->SetNumberOfThreads(1); // to produce non-random results randomImageSource->SetSize(size); randomImageSource->SetMin(200); randomImageSource->SetMax(255); randomImageSource->Update(); image->SetRegions(randomImageSource->GetOutput()->GetLargestPossibleRegion()); image->Allocate(); IndexType index; //Draw oval. for (int i=0; i<w; i++) { for (int j=0; j<h; j++) { index[0] = i; index[1] = j; if ( ((i-cx)*(i-cx)/(rx*rx) + (j-cy)*(j-cy)/(ry*ry) ) < 1) { image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)-100); } else { image->SetPixel(index, randomImageSource->GetOutput()->GetPixel(index)); } } }
}
vnl_matrix<double> computeP(double alpha, double beta, double gamma, double N) throw (int) {
double a = gamma*(2*alpha+6*beta)+1; double b = gamma*(-alpha-4*beta); double c = gamma*beta; vnl_matrix<double> P(N,N); P.fill(0); //fill diagonal P.fill_diagonal(a); //fill next two diagonals for (int i=0; i<(N-1); i++) { P(i+1,i) = b; P(i,i+1) = b; } //Moreover P(0, N-1)=b; P(N-1, 0)=b; //fill next two diagonals for (int i=0; i<(N-2); i++) { P(i+2,i) = c; P(i,i+2) = c; } //Moreover P(0, N-2)=c; P(1, N-1)=c; P(N-2, 0)=c; P(N-1, 1)=c; if ( vnl_determinant(P) == 0.0 ) { std::cerr << "Singular matrix. Determinant is 0." << std::endl; throw 2; } //Compute the inverse of the matrix P vnl_matrix< double > Pinv; Pinv = vnl_matrix_inverse< double >(P); return Pinv;
}
vnl_vector<double> sampleImage(vnl_vector<double> x, vnl_vector<double> y, OutputImageType::Pointer gradient, int position) {
int size; size = x.size(); vnl_vector<double> ans(size); IndexType index; for (int i=0; i<size; i++) { index[0] = x[i]; index[1] = y[i]; ans[i] = gradient->GetPixel(index)[position]; } return ans;
} </source>
CMakeLists.txt
<syntaxhighlight lang="cmake"> cmake_minimum_required(VERSION 3.9.5)
project(ExtractContourWithSnakes)
find_package(ITK REQUIRED) include(${ITK_USE_FILE}) if (ITKVtkGlue_LOADED)
find_package(VTK REQUIRED) include(${VTK_USE_FILE})
endif()
add_executable(ExtractContourWithSnakes MACOSX_BUNDLE ExtractContourWithSnakes.cxx)
if( "${ITK_VERSION_MAJOR}" LESS 4 )
target_link_libraries(ExtractContourWithSnakes ITKReview ${ITK_LIBRARIES})
else( "${ITK_VERSION_MAJOR}" LESS 4 )
target_link_libraries(ExtractContourWithSnakes ${ITK_LIBRARIES})
endif( "${ITK_VERSION_MAJOR}" LESS 4 )
</syntaxhighlight>
Download and Build ExtractContourWithSnakes
Click here to download ExtractContourWithSnakes and its CMakeLists.txt file. Once the tarball ExtractContourWithSnakes.tar has been downloaded and extracted,
cd ExtractContourWithSnakes/build
- If ITK is installed:
cmake ..
- If ITK is not installed but compiled on your system, you will need to specify the path to your ITK build:
cmake -DITK_DIR:PATH=/home/me/itk_build ..
Build the project:
make
and run it:
./ExtractContourWithSnakes
WINDOWS USERS PLEASE NOTE: Be sure to add the ITK bin directory to your path. This will resolve the ITK dll's at run time.
Building All of the Examples
Many of the examples in the ITK Wiki Examples Collection require VTK. You can build all of the the examples by following these instructions. If you are a new VTK user, you may want to try the Superbuild which will build a proper ITK and VTK.
ItkVtkGlue
ITK >= 4
For examples that use QuickView (which depends on VTK), you must have built ITK with Module_ITKVtkGlue=ON.
ITK < 4
Some of the ITK Examples require VTK to display the images. If you download the entire ITK Wiki Examples Collection, the ItkVtkGlue directory will be included and configured. If you wish to just build a few examples, then you will need to download ItkVtkGlue and build it. When you run cmake it will ask you to specify the location of the ItkVtkGlue binary directory.