Public Member Functions | Private Member Functions
puma2::FeatureImage< T > Class Template Reference

Superclass for all possible FeatureImages. More...

#include <FeatureImage.h>

Inheritance diagram for puma2::FeatureImage< T >:
Inheritance graph
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List of all members.

Public Member Functions

 FeatureImage (int x=0, int y=0)
 Default constructor.
 FeatureImage (int x, int y, FeatureImage *m, int xo, int yo)
 Subimage constructor.
std::vector< Feature< T > > getGlobalMaxima (int n)
 Returns the n maxima of the given image.
Feature< T > getGlobalMaximum ()
 Returns the maximum feature value.
std::vector< Feature< T > > getGlobalMinima (int n)
 Returns the n minima of the actual image.
Feature< T > getGlobalMinimum ()
 Returns the minimum feature value of the actual image.
virtual GrayLevelImage8 getGrayLevelImageRepresentation ()=0
 Returns a GrayLevelImage of the actual FeatureImage.
std::vector< Feature< T > > getLocalMaxima (int n, T threshold, int radius)
 Returns a vector of n local maxima of the actual image.
std::vector< Feature< T > > getLocalMaxima (T threshold, int radius)
 Returns a vector of all local maxima of the actual image.
std::vector< Feature< T > > getLocalMinima (int n, T threhold, int radius)
 Returns a vector of n local minima of the actual image.
std::vector< Feature< T > > getLocalMinima (T thresh, int radius)
 Returns a vector of all local minima of the actual image.
virtual ~FeatureImage ()

Private Member Functions

void createMask (int radius, bool **(&mask))
 Creates a binary mask for defining a local neighborhood.

Detailed Description

template<typename T>
class puma2::FeatureImage< T >

Superclass for all possible FeatureImages.

This class provides a superclass for all possible feature images as edge images etc. Although this class is a template class, it is abstract. So for using this class, a subclass has always to be implemented. The reason for this is an abstract method that cannot be generalized for all types of features. For scalar featuare types use the class ScalarFeatureImage instead.

Some methods of this class provide the computing of maxima and minima. These methods require the implementation of the operator <. for the features that are used. All of these methods return instances of the class Feature.

See also:
Feature
ScalarFeatureImage
Author:
Andreas Kasten <stultissimum@uni-koblenz.de>
Date:
Juli 2007

Definition at line 48 of file FeatureImage.h.


Constructor & Destructor Documentation

template<typename T>
puma2::FeatureImage< T >::FeatureImage ( int  x = 0,
int  y = 0 
) [inline]

Default constructor.

Default constructor. Creates a new image of the given size. The size is specified by the parameters x and y. The default values for both parameters are 0.

x The horizontal size of the image. y The vertical size of the image.

Definition at line 77 of file FeatureImage.h.

template<typename T>
puma2::FeatureImage< T >::FeatureImage ( int  x,
int  y,
FeatureImage< T > *  m,
int  xo,
int  yo 
) [inline]

Subimage constructor.

This is the subimage constructor. It creates a subimage of the given base image m. The size is given by the parameters x and y, the position of the subimage in the original image is given by the offsets xo and yo. The subimage will be created as a reference to the base image. The constructor will do all required checks on the sizes of the images during the creation process.

Parameters:
x,:Horizontal size of the subimage.
y,:Vertical size of the subimage.
m,:Pointer to master image of which the image becomes a subimage.
xo,:offset for horizontal position of subimage in master image.
yo,:offset for vertical position of subimage in master image.

Definition at line 98 of file FeatureImage.h.

template<typename T>
virtual puma2::FeatureImage< T >::~FeatureImage ( ) [inline, virtual]

Destructor

Definition at line 104 of file FeatureImage.h.


Member Function Documentation

template<typename T >
void puma2::FeatureImage< T >::createMask ( int  radius,
bool **&  mask 
) [private]

Creates a binary mask for defining a local neighborhood.

This method is just used for creating a radial binary mask of boolean values. The mask itself is used for searching local optima. The size of the mask is specified by the parameter radius. The created mask will be returned via call by reference, using the paramter mask.

Parameters:
radiusThe radius of the mask.
maskThe resulting binary mask.

Definition at line 640 of file FeatureImage.h.

template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getGlobalMaxima ( int  n)

Returns the n maxima of the given image.

Returns the n maxima of the given image. The maxima will be returnded as a vector of Features. For using this method, the current feature type T has to implement the operator <. Beware of using arrays as the feature type T! The operator <. will only compare the memory addresses and NOT the values.

Parameters:
nThe number of maximum values that have to be returned.
returnA vector of Features.

Definition at line 283 of file FeatureImage.h.

template<typename T >
Feature< T > puma2::FeatureImage< T >::getGlobalMaximum ( )

Returns the maximum feature value.

Returns the maximum value of the image, returned as a Feature. For using this method, the current feature type T has to implement the operator <. Beware of using arrays as the feature type T! The operator <. will only compare the memory addresses and NOT the values.

Returns:
The maximum value, given as a Feature.

Definition at line 251 of file FeatureImage.h.

template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getGlobalMinima ( int  n)

Returns the n minima of the actual image.

Returns the n minima of the actual image. The minima will be returnded as a vector of Features. For using this method, the current feature type T has to implement the operator <. Beware of using arrays as the feature type T! The operator <. will only compare the memory addresses and NOT the values.

Parameters:
nThe number of minimum values that have to be returned.
Returns:
A vector of Features.

Definition at line 360 of file FeatureImage.h.

template<typename T >
Feature< T > puma2::FeatureImage< T >::getGlobalMinimum ( )

Returns the minimum feature value of the actual image.

Returns the minimum feature value of the actual image. For using this method, the current feature type T has to implement the operator <. Beware of using arrays as the feature type T! The operator <. will only compare the memory addresses and NOT the values.

Returns:
The minimum value, given as a Feature.

Definition at line 330 of file FeatureImage.h.

template<typename T>
virtual GrayLevelImage8 puma2::FeatureImage< T >::getGrayLevelImageRepresentation ( ) [pure virtual]

Returns a GrayLevelImage of the actual FeatureImage.

Returns:
The resulting GrayLevelImage.
template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getLocalMaxima ( int  n,
threshold,
int  radius 
)

Returns a vector of n local maxima of the actual image.

Returns a vector of n local maxima of the actual image. The maxima are located within a specified range. The range itself is defined by a given radius. A value is a maximum value iff there is no other value within the range that is greater than this value. Furthermore, every maximum has to be greater than a given threhold.

Parameters:
nThe number of local maximum values that have to be returned.
thresholdThe minimum feature value that has to be reached for defining a feature as a local maximum.
radiusThe radius of the range that will be used for defining 'local'.
Returns:
A vector of Features.

Definition at line 407 of file FeatureImage.h.

template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getLocalMaxima ( threshold,
int  radius 
)

Returns a vector of all local maxima of the actual image.

Returns a vector of all local maxima of the actual image. The maxima are located within a specified range. The range itself is defined by a given radius. A value is a maximum value iff there is no other value within the range that is greater than this value. Furthermore, every maximum has to be greater than a given threhold.

Parameters:
thresholdThe minimum feature value that has to be reached for defining a feature as a local maximum.
radiusThe radius of the range that will be used for defining 'local'.
Returns:
A vector of Features.

Definition at line 477 of file FeatureImage.h.

template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getLocalMinima ( int  n,
threhold,
int  radius 
)

Returns a vector of n local minima of the actual image.

Returns a vector of n local minima of the actual image. The minima are located within a specified range. The range itself is defined by a given radius. A value is a minimum value iff there is no other value within the range that is lower than this value. Furthermore, every minimum has to be lower than a given threhold.

Parameters:
nThe number of local minimum values that have to be returned.
thresholdThe maximum feature value that has to be reached for defining a feature as a local minimum.
radiusThe radius of the range that will be used for defining 'local'.
Returns:
A vector of Features.

Definition at line 525 of file FeatureImage.h.

template<typename T >
std::vector< Feature< T > > puma2::FeatureImage< T >::getLocalMinima ( thresh,
int  radius 
)

Returns a vector of all local minima of the actual image.

Returns a vector of all local minima of the actual image. The minima are located within a specified range. The range itself is defined by a given radius. A value is a minimum value iff there is no other value within the range that is lower than this value. Furthermore, every minimum has to be lower than a given threhold.

Parameters:
thresholdThe maximum feature value that has to be reached for defining a feature as a local minimum.
radiusThe radius of the range that will be used for defining 'local'.
Returns:
A vector of Features.

Definition at line 594 of file FeatureImage.h.


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


obj_rec_gui
Author(s): AGAS/agas@uni-koblenz.de
autogenerated on Mon Oct 6 2014 02:53:43