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ITK
5.4.0
Insight Toolkit
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#include <itkHistogramToTextureFeaturesFilter.h>
This class computes texture feature coefficients from a grey level co-occurrence matrix.
This class computes features that summarize image texture, given a grey level co-occurrence matrix (generated by a ScalarImageToCooccurrenceMatrixFilter or related class).
The features calculated are as follows (where \( g(i, j) \) is the element in cell i, j of a normalized GLCM):
"Energy" \( = f_1 = \sum_{i,j}g(i, j)^2 \)
"Entropy" \( = f_2 = -\sum_{i,j}g(i, j) \log_2 g(i, j)\), or 0 if \(g(i, j) = 0\)
"Correlation" \( = f_3 = \sum_{i,j}\frac{(i - \mu)(j - \mu)g(i, j)}{\sigma^2} \)
"Difference Moment" \(= f_4 = \sum_{i,j}\frac{1}{1 + (i - j)^2}g(i, j) \)
"Inertia" \( = f_5 = \sum_{i,j}(i - j)^2g(i, j) \) (sometimes called "contrast.")
"Cluster Shade" \( = f_6 = \sum_{i,j}((i - \mu) + (j - \mu))^3 g(i, j) \)
"Cluster Prominence" \( = f_7 = \sum_{i,j}((i - \mu) + (j - \mu))^4 g(i, j) \)
"Haralick's Correlation" \( = f_8 = \frac{\sum_{i,j}(i, j) g(i, j) -\mu_t^2}{\sigma_t^2} \) where \(\mu_t\) and \(\sigma_t\) are the mean and standard deviation of the row (or column, due to symmetry) sums.
Above, \( \mu = \) (weighted pixel average) \( = \sum_{i,j}i \cdot g(i, j) = \sum_{i,j}j \cdot g(i, j) \) (due to matrix symmetry), and
\( \sigma = \) (weighted pixel variance) \( = \sum_{i,j}(i - \mu)^2 \cdot g(i, j) = \sum_{i,j}(j - \mu)^2 \cdot g(i, j) \) (due to matrix symmetry)
A good texture feature set to use is the Conners, Trivedi and Harlow set: features 1, 2, 4, 5, 6, and 7. There is some correlation between the various features, so using all of them at the same time is not necessarily a good idea.
NOTA BENE: The input histogram will be forcibly normalized! This algorithm takes three passes through the input histogram if the histogram was already normalized, and four if not.
Web references:
http://www.cssip.uq.edu.au/meastex/www/algs/algs/algs.html https://www.ucalgary.ca/~mhallbey/texture/texture_tutorial.html
Print references:
Haralick, R.M., K. Shanmugam and I. Dinstein. 1973. Textural Features for Image Classification. IEEE Transactions on Systems, Man and Cybernetics. SMC-3(6):610-620.
Haralick, R.M. 1979. Statistical and Structural Approaches to Texture. Proceedings of the IEEE, 67:786-804.
R.W. Conners and C.A. Harlow. A Theoretical Comparison of Texture Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2:204-222, 1980.
R.W. Conners, M.M. Trivedi, and C.A. Harlow. Segmentation of a High-Resolution Urban Scene using Texture Operators. Computer Vision, Graphics and Image Processing, 25:273-310, 1984.
Author: Zachary Pincus
Definition at line 133 of file itkHistogramToTextureFeaturesFilter.h.
Static Public Member Functions | |
static Pointer | New () |
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static bool | GetGlobalWarningDisplay () |
static void | GlobalWarningDisplayOff () |
static void | GlobalWarningDisplayOn () |
static Pointer | New () |
static void | SetGlobalWarningDisplay (bool val) |
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static void | BreakOnError () |
static Pointer | New () |
Protected Types | |
using | DataObjectPointerArraySizeType = ProcessObject::DataObjectPointerArraySizeType |
Private Member Functions | |
void | ComputeMeansAndVariances (double &pixelMean, double &marginalMean, double &marginalDevSquared, double &pixelVariance) |
Private Attributes | |
RelativeFrequencyContainerType | m_RelativeFrequencyContainer {} |
Additional Inherited Members | |
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static constexpr float | progressFixedToFloat (uint32_t fixed) |
static uint32_t | progressFloatToFixed (float f) |
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TimeStamp | m_OutputInformationMTime {} |
bool | m_Updating {} |
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std::atomic< int > | m_ReferenceCount {} |
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::AbsoluteFrequencyType = typename HistogramType::AbsoluteFrequencyType |
Definition at line 156 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::ConstPointer = SmartPointer<const Self> |
Definition at line 142 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::DataObjectPointer = DataObject::Pointer |
Smart Pointer type to a DataObject.
Definition at line 175 of file itkHistogramToTextureFeaturesFilter.h.
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Make a DataObject to be used for output output.
Definition at line 261 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::HistogramConstPointer = typename HistogramType::ConstPointer |
Definition at line 152 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::HistogramPointer = typename HistogramType::Pointer |
Definition at line 151 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::HistogramType = THistogram |
Definition at line 150 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::IndexType = typename HistogramType::IndexType |
Definition at line 155 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::MeasurementObjectType = SimpleDataObjectDecorator<MeasurementType> |
Type of DataObjects used for scalar outputs
Definition at line 178 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::MeasurementType = typename HistogramType::MeasurementType |
Definition at line 153 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::MeasurementVectorType = typename HistogramType::MeasurementVectorType |
Definition at line 154 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::Pointer = SmartPointer<Self> |
Definition at line 141 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::RelativeFrequencyContainerType = std::vector<RelativeFrequencyType> |
Container to hold relative frequencies of the histogram
Definition at line 164 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::RelativeFrequencyType = typename HistogramType::RelativeFrequencyType |
Definition at line 157 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::Self = HistogramToTextureFeaturesFilter |
Standard type alias
Definition at line 139 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::Superclass = ProcessObject |
Definition at line 140 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::TextureFeatureEnum = HistogramToTextureFeaturesFilterEnums::TextureFeature |
Definition at line 236 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::TotalAbsoluteFrequencyType = typename HistogramType::TotalAbsoluteFrequencyType |
Definition at line 159 of file itkHistogramToTextureFeaturesFilter.h.
using itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::TotalRelativeFrequencyType = typename HistogramType::TotalRelativeFrequencyType |
Definition at line 161 of file itkHistogramToTextureFeaturesFilter.h.
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overrideprotectedvirtual |
This method causes the filter to generate its output.
Reimplemented from itk::ProcessObject.
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetClusterProminence | ( | ) | const |
Return cluster prominence texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetClusterProminenceOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetClusterShade | ( | ) | const |
Return cluster shade texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetClusterShadeOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetCorrelation | ( | ) | const |
return correlation texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetCorrelationOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetEnergy | ( | ) | const |
Return energy texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetEnergyOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetEntropy | ( | ) | const |
Return entropy texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetEntropyOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetFeature | ( | TextureFeatureEnum | feature | ) |
convenience method to access the texture values
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetHaralickCorrelation | ( | ) | const |
Return Haralick correlation texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetHaralickCorrelationOutput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetInertia | ( | ) | const |
Return inertia texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetInertiaOutput | ( | ) | const |
const HistogramType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetInput | ( | ) | const |
MeasurementType itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetInverseDifferenceMoment | ( | ) | const |
Return inverse difference moment texture value.
const MeasurementObjectType * itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::GetInverseDifferenceMomentOutput | ( | ) | const |
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Reimplemented from itk::ProcessObject.
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Make a DataObject of the correct type to used as the specified output.
Every ProcessObject subclass must be able to create a DataObject that can be used as a specified output. This method is automatically called when DataObject::DisconnectPipeline() is called. DataObject::DisconnectPipeline, disconnects a data object from being an output of its current source. When the data object is disconnected, the ProcessObject needs to construct a replacement output data object so that the ProcessObject is in a valid state. So DataObject::DisconnectPipeline eventually calls ProcessObject::MakeOutput. Note that MakeOutput always returns a itkSmartPointer to a DataObject. ImageSource and MeshSource override this method to create the correct type of image and mesh respectively. If a filter has multiple outputs of different types, then that filter must provide an implementation of MakeOutput().
Reimplemented from itk::ProcessObject.
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standard New() method support
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Methods invoked by Print() to print information about the object including superclasses. Typically not called by the user (use Print() instead) but used in the hierarchical print process to combine the output of several classes.
Reimplemented from itk::ProcessObject.
void itk::Statistics::HistogramToTextureFeaturesFilter< THistogram >::SetInput | ( | const HistogramType * | histogram | ) |
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Definition at line 275 of file itkHistogramToTextureFeaturesFilter.h.