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Accord.NET (logo) HaralickDescriptor Class
Haralick's Texture Features.
Inheritance Hierarchy
SystemObject
  Accord.ImagingHaralickDescriptor

Namespace:  Accord.Imaging
Assembly:  Accord.Imaging (in Accord.Imaging.dll) Version: 3.4.0
Syntax
[SerializableAttribute]
public class HaralickDescriptor
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The HaralickDescriptor type exposes the following members.

Constructors
  NameDescription
Public methodHaralickDescriptor
Initializes a new instance of the HaralickDescriptor class.
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Properties
  NameDescription
Public propertyAngularSecondMomentum
Gets Haralick's first textural feature, the Angular Second Momentum, also known as Energy or Homogeneity.
Public propertyClusterProminence
Gets the Cluster Prominence textural feature.
Public propertyClusterShade
Gets the Cluster Shade textural feature.
Public propertyColumnEntropy
Gets Hy, the entropy of the ColumnMarginal vector.
Public propertyColumnMarginal
Gets the marginal probability vector obtained by summing the columns of p(i,j), given as py(j) = Σi p(i,j).
Public propertyColumnMean
Gets μ_y, the mean value of the ColumnMarginal vector.
Public propertyColumnStandardDeviation
Gets σy, the variance of the ColumnMarginal vector.
Public propertyContrast
Gets Haralick's second textural feature, the Contrast.
Public propertyCorrelation
Gets Haralick's third textural feature, the Correlation.
Public propertyDifferenceEntropy
Gets Haralick's eleventh textural feature, the Difference Entropy.
Public propertyDifferences
Gets p(x-y) (k), the sum of elements whose absolute indices diferences equals to k.
Public propertyDifferenceVariance
Gets Haralick's tenth textural feature, the Difference Variance.
Public propertyEntropy
Gets Haralick's ninth textural feature, the Entropy.
Public propertyF01
Gets Haralick's first textural feature, the Angular Second Momentum.
Public propertyF02
Gets Haralick's second textural feature, the Contrast.
Public propertyF03
Gets Haralick's third textural feature, the Correlation.
Public propertyF04
Gets Haralick's fourth textural feature, the Sum of Squares: Variance.
Public propertyF05
Gets Haralick's fifth textural feature, the Inverse Difference Moment.
Public propertyF06
Gets Haralick's sixth textural feature, the Sum Average.
Public propertyF07
Gets Haralick's seventh textural feature, the Sum Variance.
Public propertyF08
Gets Haralick's eighth textural feature, the Sum Entropy.
Public propertyF09
Gets Haralick's ninth textural feature, the Entropy.
Public propertyF10
Gets Haralick's tenth textural feature, the Difference Variance.
Public propertyF11
Gets Haralick's eleventh textural feature, the Difference Entropy.
Public propertyF12
Gets Haralick's twelfth textural feature, the First Information Measure.
Public propertyF13
Gets Haralick's thirteenth textural feature, the Second Information Measure.
Public propertyF14
Gets Haralick's fourteenth textural feature, the Maximal Correlation Coefficient.
Public propertyFirstInformationMeasure
Gets Haralick's twelfth textural feature, the First Information Measure.
Public propertyGrayLevels
Gets the number of gray levels in the original image. This is the number of dimensions of the co-occurrence matrix.
Public propertyInverseDifferenceMoment
Gets Haralick's fifth textural feature, the Inverse Difference Moment, also known as Local Homogeneity. Can be regarded as a complement to Contrast.
Public propertyLaplaceContrast
Gets a variation of Haralick's second textural feature, the Contrast with Absolute values (instead of squares).
Public propertyMaximalCorrelationCoefficient
Gets Haralick's fourteenth textural feature, the Maximal Correlation Coefficient.
Public propertyMean
Gets the matrix mean μ.
Public propertyRowEntropy
Gets Hx, the entropy of the RowMarginal vector.
Public propertyRowMarginal
Gets the marginal probability vector obtained by summing the rows of p(i,j), given as px(i) = Σj p(i,j).
Public propertyRowMean
Gets μx, the mean value of the RowMarginal vector.
Public propertyRowStandardDeviation
Gets σx, the variance of the RowMarginal vector.
Public propertySecondInformationMeasure
Gets Haralick's thirteenth textural feature, the Second Information Measure.
Public propertySum
Gets the matrix sum.
Public propertySumAverage
Gets Haralick's sixth textural feature, the Sum Average.
Public propertySumEntropy
Gets Haralick's eighth textural feature, the Sum Entropy.
Public propertySumOfSquares
Gets Haralick's fourth textural feature, the Sum of Squares: Variance.
Public propertySums
Gets p(x+y)(k), the sum of elements whose indices sum to k.
Public propertySumVariance
Gets Haralick's seventh textural feature, the Sum Variance.
Public propertyTextureHomogeneity
Gets a variation of Haralick's fifth textural feature, the Texture Homogeneity. Can be regarded as a complement to LaplaceContrast.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetVector
Creates a feature vector with the chosen feature functions.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodToTOverloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
Public Extension MethodToTOverloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by Matrix.)
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Remarks

Haralick's texture features are based on measures derived from Gray-level Co-occurrence matrices (GLCM).

Whether considering the intensity or grayscale values of the image or various dimensions of color, the co-occurrence matrix can measure the texture of the image. Because co-occurrence matrices are typically large and sparse, various metrics of the matrix are often taken to get a more useful set of features. Features generated using this technique are usually called Haralick features, after R. M. Haralick, attributed to his paper Textural features for image classification (1973).

This class encompasses most of the features derived on Haralick's original paper. All features are lazy-evaluated until needed; but may also be combined in a single feature vector by calling GetVector(Int32).

References:

See Also