This class implements simple clustering functions for image information. More...

Data Structures
class	Cluster
	This class implements a single cluster for 3 channel 24 bit data objects. More...

class	Data
	This class implements a single data to be clustered. More...

class	Segmentation
	This class implements the management of clusters. More...

Public Types
typedef std::vector< Data >	Datas
	Definition of a vector holding data object. More...

typedef std::vector< Cluster >	Clusters
	Definition of a vector holding cluster objects. More...

Static Public Member Functions
static Segmentation	findRandomClusteringOneIteration (const Datas &datas, const unsigned int clusterRadius, RandomGenerator &randomGenerator, const size_t expectedClusters=20)
	Determines a random cluster for data elements by application of one seeking iteration. More...

static Segmentation	findRandomClusteringTwoIterations (const Datas &datas, const unsigned int clusterRadius, RandomGenerator &randomGenerator, const size_t expectedClusters=20)
	Determines a random cluster for data elements by application of two seeking iterations. More...

static Segmentation	findOptimalRandomClustering (const Datas &datas, const unsigned int clusterRadius, RandomGenerator &randomGenerator, const unsigned int iterations=10u, Worker *worker=nullptr, const bool oneIteration=true)
	Determines an optimal cluster from a set of random clusters for 3 channel 24 bit data elements. More...

Static Private Member Functions
static void	findOptimalRandomClusteringSubset (const Datas datas, const unsigned int clusterRadius, RandomGenerator randomGenerator, Segmentation *segmentation, const bool oneIteration, const unsigned int firstIteration, const unsigned int numberIterations, const unsigned int iterationIndex)
	Determines an optimal cluster from a set of random clusters for 3 channel 24 bit data elements. More...

Detailed Description

template<unsigned int tChannels>
class Ocean::CV::Segmentation::Clustering< tChannels >

This class implements simple clustering functions for image information.

Template Parameters

tChannels The number of data channels of the image information to be clustered, with range [1, infinity)

Member Typedef Documentation

◆ Clusters

template<unsigned int tChannels>

typedef std::vector<Cluster> Ocean::CV::Segmentation::Clustering< tChannels >::Clusters

Definition of a vector holding cluster objects.

◆ Datas

template<unsigned int tChannels>

typedef std::vector<Data> Ocean::CV::Segmentation::Clustering< tChannels >::Datas

Definition of a vector holding data object.

Member Function Documentation

◆ findOptimalRandomClustering()

template<unsigned int tChannels>

Clustering< tChannels >::Segmentation Ocean::CV::Segmentation::Clustering< tChannels >::findOptimalRandomClustering	(	const Datas &	datas,
		const unsigned int	clusterRadius,
		RandomGenerator &	randomGenerator,
		const unsigned int	iterations = `10u`,
		Worker *	worker = `nullptr`,
		const bool	oneIteration = `true`
	)

static

Determines an optimal cluster from a set of random clusters for 3 channel 24 bit data elements.

Parameters

datas	The data objects to distribute into clusters
clusterRadius	Radius of a single cluster
randomGenerator	Random number generator
iterations	The number of clustering steps, with range [1, infinity)
worker	Optional worker object to distribute the computation
oneIteration	State determining whether one ore two seeking iterations are applied for each individual clustering step

Returns: Resulting optimal segmentation with clusters

◆ findOptimalRandomClusteringSubset()

template<unsigned int tChannels>

void Ocean::CV::Segmentation::Clustering< tChannels >::findOptimalRandomClusteringSubset	(	const Datas *	datas,
		const unsigned int	clusterRadius,
		RandomGenerator *	randomGenerator,
		Segmentation *	segmentation,
		const bool	oneIteration,
		const unsigned int	firstIteration,
		const unsigned int	numberIterations,
		const unsigned int	iterationIndex
	)

staticprivate

Determines an optimal cluster from a set of random clusters for 3 channel 24 bit data elements.

Parameters

datas	The data objects to distribute into clusters
clusterRadius	Radius of a single cluster
randomGenerator	Random number generator
segmentation	Resulting optimal segmentation
oneIteration	State determining whether one or two seeking iterations are executed for each clustering
firstIteration	First iteration to be handled
numberIterations	Number iterations to be handled
iterationIndex	Iteration index

◆ findRandomClusteringOneIteration()

template<unsigned int tChannels>

Clustering< tChannels >::Segmentation Ocean::CV::Segmentation::Clustering< tChannels >::findRandomClusteringOneIteration	(	const Datas &	datas,
		const unsigned int	clusterRadius,
		RandomGenerator &	randomGenerator,
		const size_t	expectedClusters = `20`
	)

static

Determines a random cluster for data elements by application of one seeking iteration.

Parameters

datas	The data objects to distribute into clusters
clusterRadius	Radius of each cluster
randomGenerator	Random number generator
expectedClusters	Optional number of expected clusters allowing to reserve enough space in the beginning

Returns: Resulting segmentation with clusters

◆ findRandomClusteringTwoIterations()

template<unsigned int tChannels>

Clustering< tChannels >::Segmentation Ocean::CV::Segmentation::Clustering< tChannels >::findRandomClusteringTwoIterations	(	const Datas &	datas,
		const unsigned int	clusterRadius,
		RandomGenerator &	randomGenerator,
		const size_t	expectedClusters = `20`
	)

static

Determines a random cluster for data elements by application of two seeking iterations.

The first iteration determines all elements belonging to a randomly selected cluster element.
The second iteration seeks all element belonging to the average data as determined by the first iteration.

Parameters

datas	The data objects to distribute into clusters
clusterRadius	Radius of each cluster
randomGenerator	Random number generator
expectedClusters	Optional number of expected clusters allowing to reserve enough space in the beginning

Returns: Resulting segmentation with clusters

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

Clustering.h

Data Structures

Public Types

Static Public Member Functions

Static Private Member Functions

Detailed Description

template<unsigned int tChannels> class Ocean::CV::Segmentation::Clustering< tChannels >

Member Typedef Documentation

◆ Clusters

◆ Datas

Member Function Documentation

◆ findOptimalRandomClustering()

◆ findOptimalRandomClusteringSubset()

◆ findRandomClusteringOneIteration()

◆ findRandomClusteringTwoIterations()

template<unsigned int tChannels>
class Ocean::CV::Segmentation::Clustering< tChannels >