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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkZeroCrossingBasedEdgeDetectionImageFilter.h,v $
Language: C++
Date: $Date: 2007-06-29 00:10:17 $
Version: $Revision: 1.17 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef __itkZeroCrossingBasedEdgeDetectionImageFilter_h
#define __itkZeroCrossingBasedEdgeDetectionImageFilter_h
#include "itkImageToImageFilter.h"
#include "itkFixedArray.h"
#include "itkImage.h"
namespace itk
{
/** \class ZeroCrossingBasedEdgeDetectionImageFilter
*
* This filter implements a zero-crossing based edge detecor. The zero-crossing
* based edge detector looks for pixels in the Laplacian of an image where the
* value of the Laplacian passes through zero --- points where the Laplacian
* changes sign. Such points often occur at ``edges'' in images ---
* i.e. points where the intensity of the image changes rapidly, but they also
* occur at places that are not as easy to associate with edges. It is best to
* think of the zero crossing detector as some sort of feature detector rather
* than as a specific edge detector.
*
* /par
* Zero crossings always lie on closed contours and so the output from the zero
* crossing detector is usually a binary image with single pixel thickness
* lines showing the positions of the zero crossing points.
*
* /par
* In this implementation, the input image is first smoothed with a Gaussian
* filter, then the LaplacianImageFilter is applied to smoothed image. Finally
* the zero-crossing of the Laplacian of the smoothed image is detected. The
* output is a binary image.
*
* /par Inputs and Outputs
* The input to the filter should be a scalar, itk::Image of arbitrary
* dimension. The output image is a binary, labeled image. See
* itkZeroCrossingImageFilter for more information on requirements of the data
* type of the output.
*
* /par
* To use this filter, first set the parameters (variance and maximum error)
* needed by the embedded DiscreteGaussianImageFilter, i.e. See
* DiscreteGaussianImageFilter for information about these parameters.
* Optionally, you may also set foreground and background values for the
* zero-crossing filter. The default label values are Zero for the background
* and One for the foreground, as defined in NumericTraits for the data type of
* the output image.
*
* \sa DiscreteGaussianImageFilter
* \sa LaplacianImageFilter
* \sa ZeroCrossingImageFilter
* \ingroup ImageFeatureExtraction */
template<class TInputImage, class TOutputImage>
class ITK_EXPORT ZeroCrossingBasedEdgeDetectionImageFilter
: public ImageToImageFilter<TInputImage, TOutputImage>
{
public:
/** Standard "Self" & Superclass typedef. */
typedef ZeroCrossingBasedEdgeDetectionImageFilter Self;
typedef ImageToImageFilter<TInputImage, TOutputImage> Superclass;
/** Image typedef support */
typedef TInputImage InputImageType;
typedef TOutputImage OutputImageType;
/** SmartPointer typedef support */
typedef SmartPointer<Self> Pointer;
typedef SmartPointer<const Self> ConstPointer;
/** Define pixel type */
typedef typename TInputImage::PixelType InputImagePixelType;
typedef typename TOutputImage::PixelType OutputImagePixelType;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Typedef to describe the output image region type. */
typedef typename TOutputImage::RegionType OutputImageRegionType;
/** Run-time type information (and related methods). */
itkTypeMacro(ZeroCrossingBasedEdgeDetectionImageFilter, ImageToImageFilter);
/** ImageDimension enumeration */
itkStaticConstMacro(ImageDimension, unsigned int,
TInputImage::ImageDimension );
itkStaticConstMacro(OutputImageDimension, unsigned int,
TOutputImage::ImageDimension );
/** Typedef of double containers */
typedef FixedArray<double, itkGetStaticConstMacro(ImageDimension)> ArrayType;
/** Standard get/set macros for Gaussian filter parameters. */
itkSetMacro(Variance, ArrayType);
itkGetMacro(Variance, const ArrayType);
itkSetMacro(MaximumError, ArrayType);
itkGetMacro(MaximumError, const ArrayType);
/** Get/Set the label values for the ZeroCrossingImageFilter */
itkGetMacro(BackgroundValue, OutputImagePixelType);
itkSetMacro(BackgroundValue, OutputImagePixelType);
itkGetMacro(ForegroundValue, OutputImagePixelType);
itkSetMacro(ForegroundValue, OutputImagePixelType);
/** Set the variance parameter needed by the embedded gaussian filter */
void SetVariance(const typename ArrayType::ValueType v)
{
m_Variance.Fill(v);
}
/** Set the MaximumError parameter needed by the embedded gaussian filter
* This value is used to set the desired maximum error of the gaussian
* approximation. Maximum error is the difference between the area under the
* discrete Gaussian curve and the area under the continuous Gaussian. Maximum
* error affects the Gaussian operator size. The value must be between 0.0 and
* 1.0. */
void SetMaximumError(const typename ArrayType::ValueType v)
{
m_MaximumError.Fill(v);
}
#ifdef ITK_USE_CONCEPT_CHECKING
/** Begin concept checking */
itkConceptMacro(OutputEqualityComparableCheck,
(Concept::EqualityComparable<OutputImagePixelType>));
itkConceptMacro(SameDimensionCheck,
(Concept::SameDimension<ImageDimension, OutputImageDimension>));
itkConceptMacro(SameTypeCheck,
(Concept::SameType<InputImagePixelType, OutputImagePixelType>));
itkConceptMacro(OutputOStreamWritableCheck,
(Concept::OStreamWritable<OutputImagePixelType>));
itkConceptMacro(PixelTypeIsFloatingPointCheck,
(Concept::IsFloatingPoint<InputImagePixelType>));
/** End concept checking */
#endif
protected:
ZeroCrossingBasedEdgeDetectionImageFilter()
{
m_Variance.Fill(1.0);
m_MaximumError.Fill(0.01);
m_BackgroundValue = NumericTraits<OutputImagePixelType>::Zero;
m_ForegroundValue = NumericTraits<OutputImagePixelType>::One;
}
~ZeroCrossingBasedEdgeDetectionImageFilter(){}
ZeroCrossingBasedEdgeDetectionImageFilter(const Self&) {}
void PrintSelf(std::ostream& os, Indent indent) const;
/** Standard pipeline method. While this class does not implement a
* ThreadedGenerateData(), its GenerateData() delegates all
* calculations to the pipeline of a DiscreteGaussianImageFilter,
* a LaplacianImageFilter and a ZeroCrossingImageFilter. Since these
* filters are multithreaded, this filter is multithreaded by default.
*/
void GenerateData();
private:
/** The variance of the Gaussian Filter used in this filter */
ArrayType m_Variance;
/** The maximum error of the gaussian blurring kernel in each dimensional
* direction. */
ArrayType m_MaximumError;
OutputImagePixelType m_BackgroundValue;
OutputImagePixelType m_ForegroundValue;
};
} //end of namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
#include "itkZeroCrossingBasedEdgeDetectionImageFilter.txx"
#endif
#endif
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