te::rp::ClassifierKMeansStrategy Class Reference

KMeans strategy for image classification. Step-by-step: More...

#include <ClassifierKMeansStrategy.h>

Inheritance diagram for te::rp::ClassifierKMeansStrategy:

Classes
class	Parameters
	Classifier Parameters. More...

Public Member Functions
	ClassifierKMeansStrategy ()
bool	execute (const te::rst::Raster &inputRaster, const std::vector< unsigned int > &inputRasterBands, const std::vector< te::gm::Polygon * > &inputPolygons, te::rst::Raster &outputRaster, const unsigned int outputRasterBand, const bool enableProgressInterface) throw (te::rp::Exception)
	Executes the classification strategy. More...
std::vector< int >	getOutputDataTypes () const
	Returns the output raster pixel data type for each output band. More...
bool	initialize (ClassifierStrategyParameters const *const strategyParams) throw (te::rp::Exception)
	Initialize the classification strategy. More...
	~ClassifierKMeansStrategy ()

Protected Attributes
bool	m_isInitialized
	True if this instance is initialized. More...
ClassifierKMeansStrategy::Parameters	m_parameters
	Internal execution parameters. More...

Detailed Description

KMeans strategy for image classification. Step-by-step:

1. Define a random solution, creating K values of mean.
2. Classify each pixel according to the closest mean.
3. Calculate new means using the classified pixels.
4. Go back to step 2, or stop depending on the following checks:
5. Check if the new means are different from the previous iteration, using the convergence threshold.
6. Check if maximum number of iterations has achieved.

Definition at line 52 of file ClassifierKMeansStrategy.h.

Constructor & Destructor Documentation

te::rp::ClassifierKMeansStrategy::ClassifierKMeansStrategy

(

)

te::rp::ClassifierKMeansStrategy::~ClassifierKMeansStrategy

(

)

Member Function Documentation

bool te::rp::ClassifierKMeansStrategy::execute ( const te::rst::Raster &  inputRaster, const std::vector< unsigned int > &  inputRasterBands, const std::vector< te::gm::Polygon * > &  inputPolygons, te::rst::Raster &  outputRaster, const unsigned int  outputRasterBand, const bool  enableProgressInterface  ) throw ( te::rp::Exception )

virtual

Executes the classification strategy.

Parameters

inputRaster	Input raster.
inputRasterBands	Input raster bands.
inputPolygons	The polygons to be classified when using object-based image analysis (OBIA).
outputRaster	Output raster.
outputRasterBand	Output raster band.
enableProgressInterface	Enable the internal strategy to update the progress interface.

Returns

true if OK, false on errors.

Implements te::rp::ClassifierStrategy.

std::vector< int > te::rp::ClassifierKMeansStrategy::getOutputDataTypes ( ) const

virtual

Returns the output raster pixel data type for each output band.

Returns

Returns the output raster pixel data type for each output band.

Implements te::rp::ClassifierStrategy.

bool te::rp::ClassifierKMeansStrategy::initialize ( ClassifierStrategyParameters const *const  strategyParams ) throw ( te::rp::Exception )

virtual

Initialize the classification strategy.

Parameters

strategyParams

A pointer to the user given specific classification strategy parameters ou NULL if no parameters are present.

Returns

true if OK, false on errors.

Implements te::rp::ClassifierStrategy.

Member Data Documentation

bool te::rp::ClassifierKMeansStrategy::m_isInitialized

protected

True if this instance is initialized.

Definition at line 103 of file ClassifierKMeansStrategy.h.

ClassifierKMeansStrategy::Parameters te::rp::ClassifierKMeansStrategy::m_parameters

protected

Internal execution parameters.

Definition at line 104 of file ClassifierKMeansStrategy.h.

---

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

• /home/castejon/castejon_files/develop/terralib5/git_master/terralib5/src/terralib/rp/ClassifierKMeansStrategy.h