/usr/include/vtk-5.8/vtkImageEuclideanDistance.h is in libvtk5-dev 5.8.0-17.5.
This file is owned by root:root, with mode 0o644.
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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 | /*=========================================================================
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 "vtkImageDecomposeFilter.h"
#define VTK_EDT_SAITO_CACHED 0
#define VTK_EDT_SAITO 1
class VTK_IMAGING_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);
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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