#include <itkOtsuMultipleThresholdsCalculator.h>

Inheritance diagram for itk::OtsuMultipleThresholdsCalculator< TInputHistogram >:

Collaboration diagram for itk::OtsuMultipleThresholdsCalculator< TInputHistogram >:

Public Types
using	ConstPointer = SmartPointer< const Self >

using	FrequencyType = typename TInputHistogram::AbsoluteFrequencyType

using	FrequencyVectorType = std::vector< FrequencyType >

using	InstanceIdentifierType = typename TInputHistogram::InstanceIdentifier

using	InstanceIdentifierVectorType = std::vector< InstanceIdentifierType >

using	MeanType = typename NumericTraits< MeasurementType >::RealType

using	MeanVectorType = std::vector< MeanType >

using	MeasurementType = typename TInputHistogram::MeasurementType

using	Pointer = SmartPointer< Self >

using	Self = OtsuMultipleThresholdsCalculator

using	Superclass = HistogramAlgorithmBase< TInputHistogram >

using	VarianceType = typename NumericTraits< MeasurementType >::RealType

using	WeightType = typename NumericTraits< MeasurementType >::RealType

using	WeightVectorType = std::vector< WeightType >

Public Types inherited from itk::HistogramAlgorithmBase< TInputHistogram >
using	ConstPointer = SmartPointer< const Self >

using	InputHistogramType = TInputHistogram

using	Pointer = SmartPointer< Self >

using	Self = HistogramAlgorithmBase

using	Superclass = Object

Public Types inherited from itk::Object
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = Object

using	Superclass = LightObject

Public Types inherited from itk::LightObject
using	ConstPointer = SmartPointer< const Self >

using	Pointer = SmartPointer< Self >

using	Self = LightObject

using	OutputType = std::vector< MeasurementType >

SizeValueType	m_NumberOfThresholds { 1 }

OutputType	m_Output

bool	m_ValleyEmphasis { false }

bool	m_ReturnBinMidpoint { false }

virtual const char *	GetNameOfClass () const

virtual ::itk::LightObject::Pointer	CreateAnother () const

const OutputType &	GetOutput ()

virtual void	SetNumberOfThresholds (SizeValueType _arg)

virtual SizeValueType	GetNumberOfThresholds () const

void	Compute () override

virtual void	SetValleyEmphasis (bool _arg)

virtual const bool &	GetValleyEmphasis () const

virtual void	ValleyEmphasisOn ()

virtual void	ValleyEmphasisOff ()

virtual void	SetReturnBinMidpoint (bool _arg)

virtual const bool &	GetReturnBinMidpoint () const

virtual void	ReturnBinMidpointOn ()

virtual void	ReturnBinMidpointOff ()

static Pointer	New ()

	OtsuMultipleThresholdsCalculator ()

	~OtsuMultipleThresholdsCalculator () override=default

void	PrintSelf (std::ostream &os, Indent indent) const override

bool	IncrementThresholds (InstanceIdentifierVectorType &thresholdIndexes, MeanType globalMean, MeanVectorType &classMean, FrequencyVectorType &classFrequency)

Additional Inherited Members
Public Member Functions inherited from itk::HistogramAlgorithmBase< TInputHistogram >
void	SetInputHistogram (const TInputHistogram *histogram)

const TInputHistogram *	GetInputHistogram () const

Public Member Functions inherited from itk::Object
unsigned long	AddObserver (const EventObject &event, Command *)

unsigned long	AddObserver (const EventObject &event, Command *) const

unsigned long	AddObserver (const EventObject &event, std::function< void(const EventObject &)> function) const

virtual void	DebugOff () const

virtual void	DebugOn () const

Command *	GetCommand (unsigned long tag)

bool	GetDebug () const

MetaDataDictionary &	GetMetaDataDictionary ()

const MetaDataDictionary &	GetMetaDataDictionary () const

virtual ModifiedTimeType	GetMTime () const

virtual const TimeStamp &	GetTimeStamp () const

bool	HasObserver (const EventObject &event) const

void	InvokeEvent (const EventObject &)

void	InvokeEvent (const EventObject &) const

virtual void	Modified () const

void	Register () const override

void	RemoveAllObservers ()

void	RemoveObserver (unsigned long tag)

void	SetDebug (bool debugFlag) const

void	SetReferenceCount (int) override

void	UnRegister () const noexcept override

void	SetMetaDataDictionary (const MetaDataDictionary &rhs)

void	SetMetaDataDictionary (MetaDataDictionary &&rrhs)

virtual void	SetObjectName (std::string _arg)

virtual const std::string &	GetObjectName () const

Public Member Functions inherited from itk::LightObject
Pointer	Clone () const

virtual void	Delete ()

virtual int	GetReferenceCount () const

void	Print (std::ostream &os, Indent indent=0) const

Static Public Member Functions inherited from itk::Object
static bool	GetGlobalWarningDisplay ()

static void	GlobalWarningDisplayOff ()

static void	GlobalWarningDisplayOn ()

static Pointer	New ()

static void	SetGlobalWarningDisplay (bool val)

Static Public Member Functions inherited from itk::LightObject
static void	BreakOnError ()

static Pointer	New ()

Protected Member Functions inherited from itk::HistogramAlgorithmBase< TInputHistogram >
	HistogramAlgorithmBase ()

	~HistogramAlgorithmBase () override=default

Protected Member Functions inherited from itk::Object
	Object ()

	~Object () override

bool	PrintObservers (std::ostream &os, Indent indent) const

virtual void	SetTimeStamp (const TimeStamp &timeStamp)

Protected Member Functions inherited from itk::LightObject
virtual LightObject::Pointer	InternalClone () const

	LightObject ()

virtual void	PrintHeader (std::ostream &os, Indent indent) const

virtual void	PrintTrailer (std::ostream &os, Indent indent) const

virtual	~LightObject ()

Protected Attributes inherited from itk::LightObject
std::atomic< int >	m_ReferenceCount

Detailed Description

template<typename TInputHistogram>
class itk::OtsuMultipleThresholdsCalculator< TInputHistogram >

Computes Otsu's multiple thresholds for a histogram.

You plug in the target histogram using SetInputHistogram method and specify the number of thresholds you want to be computed. Then call the Compute() method to run the algorithm.

The thresholds are computed so that the between-class variance is maximized.

This calculator also includes an option to use the valley emphasis algorithm from H.F. Ng, "Automatic thresholding for defect detection", Pattern Recognition Letters, (27): 1644-1649, 2006. The valley emphasis algorithm is particularly effective when the object to be thresholded is small. See the following tests for examples: itkOtsuMultipleThresholdsImageFilterTest3 and itkOtsuMultipleThresholdsImageFilterTest4 To use this algorithm, simple call the setter: SetValleyEmphasis(true) It is turned off by default.

Examples: Examples/Filtering/OtsuMultipleThresholdImageFilter.cxx.

Definition at line 50 of file itkOtsuMultipleThresholdsCalculator.h.