/usr/include/vtk-6.2/vtkImageEuclideanDistance.h is in libvtk6-dev 6.2.0+dfsg1-10build1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | /*=========================================================================
Program: Visualization Toolkit
Module: vtkImageEuclideanDistance.h
Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
All rights reserved.
See Copyright.txt or http://www.kitware.com/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 notice for more information.
=========================================================================*/
// .NAME vtkImageEuclideanDistance - computes 3D Euclidean DT
// .SECTION Description
// vtkImageEuclideanDistance implements the Euclidean DT using
// Saito's algorithm. The distance map produced contains the square of the
// Euclidean distance values.
//
// The algorithm has a o(n^(D+1)) complexity over nxnx...xn images in D
// dimensions. It is very efficient on relatively small images. Cuisenaire's
// algorithms should be used instead if n >> 500. These are not implemented
// yet.
//
// For the special case of images where the slice-size is a multiple of
// 2^N with a large N (typically for 256x256 slices), Saito's algorithm
// encounters a lot of cache conflicts during the 3rd iteration which can
// slow it very significantly. In that case, one should use
// ::SetAlgorithmToSaitoCached() instead for better performance.
//
// References:
//
// T. Saito and J.I. Toriwaki. New algorithms for Euclidean distance
// transformations of an n-dimensional digitised picture with applications.
// Pattern Recognition, 27(11). pp. 1551--1565, 1994.
//
// O. Cuisenaire. Distance Transformation: fast algorithms and applications
// to medical image processing. PhD Thesis, Universite catholique de Louvain,
// October 1999. http://ltswww.epfl.ch/~cuisenai/papers/oc_thesis.pdf
#ifndef vtkImageEuclideanDistance_h
#define vtkImageEuclideanDistance_h
#include "vtkImagingGeneralModule.h" // For export macro
#include "vtkImageDecomposeFilter.h"
#define VTK_EDT_SAITO_CACHED 0
#define VTK_EDT_SAITO 1
class VTKIMAGINGGENERAL_EXPORT vtkImageEuclideanDistance : public vtkImageDecomposeFilter
{
public:
static vtkImageEuclideanDistance *New();
vtkTypeMacro(vtkImageEuclideanDistance,vtkImageDecomposeFilter);
void PrintSelf(ostream& os, vtkIndent indent);
// Description:
// Used internally for streaming and threads.
// Splits output update extent into num pieces.
// This method needs to be called num times. Results must not overlap for
// consistent starting extent. Subclass can override this method.
// This method returns the number of peices resulting from a
// successful split. This can be from 1 to "total".
// If 1 is returned, the extent cannot be split.
int SplitExtent(int splitExt[6], int startExt[6],
int num, int total);
// Description:
// Used to set all non-zero voxels to MaximumDistance before starting
// the distance transformation. Setting Initialize off keeps the current
// value in the input image as starting point. This allows to superimpose
// several distance maps.
vtkSetMacro(Initialize, int);
vtkGetMacro(Initialize, int);
vtkBooleanMacro(Initialize, int);
// Description:
// Used to define whether Spacing should be used in the computation of the
// distances
vtkSetMacro(ConsiderAnisotropy, int);
vtkGetMacro(ConsiderAnisotropy, int);
vtkBooleanMacro(ConsiderAnisotropy, int);
// Description:
// Any distance bigger than this->MaximumDistance will not ne computed but
// set to this->MaximumDistance instead.
vtkSetMacro(MaximumDistance, double);
vtkGetMacro(MaximumDistance, double);
// Description:
// Selects a Euclidean DT algorithm.
// 1. Saito
// 2. Saito-cached
// More algorithms will be added later on.
vtkSetMacro(Algorithm, int);
vtkGetMacro(Algorithm, int);
void SetAlgorithmToSaito ()
{ this->SetAlgorithm(VTK_EDT_SAITO); }
void SetAlgorithmToSaitoCached ()
{ this->SetAlgorithm(VTK_EDT_SAITO_CACHED); }
virtual int IterativeRequestData(vtkInformation*,
vtkInformationVector**,
vtkInformationVector*);
protected:
vtkImageEuclideanDistance();
~vtkImageEuclideanDistance() {}
double MaximumDistance;
int Initialize;
int ConsiderAnisotropy;
int Algorithm;
// Replaces "EnlargeOutputUpdateExtent"
virtual void AllocateOutputScalars(vtkImageData *outData,
int outExt[6],
vtkInformation* outInfo);
virtual int IterativeRequestInformation(vtkInformation* in,
vtkInformation* out);
virtual int IterativeRequestUpdateExtent(vtkInformation* in,
vtkInformation* out);
private:
vtkImageEuclideanDistance(const vtkImageEuclideanDistance&); // Not implemented.
void operator=(const vtkImageEuclideanDistance&); // Not implemented.
};
#endif
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