viennals::DetectFeatures< T, D > Class Template Reference

This class detects features of the level set function. This class offers two methods to determine features of the surface: based on the mean curvature, and based on the angle between surface normals. The curvature-based algorithm is the default as it leads to more accurate results and should be preferred in general. More...

#include <lsDetectFeatures.hpp>

Public Member Functions
	DetectFeatures ()
	DetectFeatures (SmartPointer< Domain< T, D > > passedLevelSet)
	DetectFeatures (SmartPointer< Domain< T, D > > passedLevelSet, T passedLimit)
	DetectFeatures (SmartPointer< Domain< T, D > > passedLevelSet, T passedLimit, FeatureDetectionEnum passedMethod)
void	setDetectionThreshold (T threshold)
void	setDetectionMethod (FeatureDetectionEnum passedMethod)
	Set which algorithm to use to detect features. The curvature-based algorithm should always be preferred, while the normals-based algorithm is just provided for experimental use.
void	apply ()
	Execute the algorithm.

Static Public Attributes
static constexpr char	featureMarkersLabel [] = "FeatureMarkers"

Detailed Description

template<class T, int D>
class viennals::DetectFeatures< T, D >

This class detects features of the level set function. This class offers two methods to determine features of the surface: based on the mean curvature, and based on the angle between surface normals. The curvature-based algorithm is the default as it leads to more accurate results and should be preferred in general.

Constructor & Destructor Documentation

DetectFeatures() [1/4]

template<class T , int D>

viennals::DetectFeatures< T, D >::DetectFeatures ( )

inline

DetectFeatures() [2/4]

template<class T , int D>

viennals::DetectFeatures< T, D >::DetectFeatures ( SmartPointer< Domain< T, D > > passedLevelSet )

inline

DetectFeatures() [3/4]

template<class T , int D>

viennals::DetectFeatures< T, D >::DetectFeatures ( SmartPointer< Domain< T, D > > passedLevelSet, T passedLimit )

inline

DetectFeatures() [4/4]

template<class T , int D>

viennals::DetectFeatures< T, D >::DetectFeatures ( SmartPointer< Domain< T, D > > passedLevelSet, T passedLimit, FeatureDetectionEnum passedMethod )

inline

Member Function Documentation

apply()

template<class T , int D>

void viennals::DetectFeatures< T, D >::apply ( )

inline

Execute the algorithm.

setDetectionMethod()

template<class T , int D>

void viennals::DetectFeatures< T, D >::setDetectionMethod ( FeatureDetectionEnum passedMethod )

inline

Set which algorithm to use to detect features. The curvature-based algorithm should always be preferred, while the normals-based algorithm is just provided for experimental use.

setDetectionThreshold()

template<class T , int D>

void viennals::DetectFeatures< T, D >::setDetectionThreshold ( T threshold )

inline

Member Data Documentation

featureMarkersLabel

template<class T , int D>

char viennals::DetectFeatures< T, D >::featureMarkersLabel[] = "FeatureMarkers"

staticconstexpr

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The documentation for this class was generated from the following file:

• include/viennals/lsDetectFeatures.hpp