HALCON 18.05 / HALCON Operator Reference / Image / Features
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fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropy (Operator)

Name

fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropy — Determine the fuzzy entropy of regions.

Signature

fuzzy_entropy(Regions, Image : : Apar, Cpar : Entropy)

Herror fuzzy_entropy(const Hobject Regions, const Hobject Image, const Hlong Apar, const Hlong Cpar, double* Entropy)

Herror T_fuzzy_entropy(const Hobject Regions, const Hobject Image, const Htuple Apar, const Htuple Cpar, Htuple* Entropy)

void FuzzyEntropy(const HObject& Regions, const HObject& Image, const HTuple& Apar, const HTuple& Cpar, HTuple* Entropy)

HTuple HImage::FuzzyEntropy(const HRegion& Regions, Hlong Apar, Hlong Cpar) const

HTuple HRegion::FuzzyEntropy(const HImage& Image, Hlong Apar, Hlong Cpar) const

static void HOperatorSet.FuzzyEntropy(HObject regions, HObject image, HTuple apar, HTuple cpar, out HTuple entropy)

HTuple HImage.FuzzyEntropy(HRegion regions, int apar, int cpar)

HTuple HRegion.FuzzyEntropy(HImage image, int apar, int cpar)

Description

fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropyFuzzyEntropy calculates the fuzzy entropy of a fuzzy set. To do so, the image is regarded as a fuzzy set. The entropy then is a measure of how well the image approximates a white or black image. It is defined as follows:

where MxN is the size of the image, and h(l) is the histogram of the image. Furthermore,
Here, u(x(m,n)) is a fuzzy membership function defining the fuzzy set (see fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeter). The same restrictions hold as in fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeter.

Attention

Note that for fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropyFuzzyEntropy, the RegionsRegionsRegionsRegionsregions must lie completely within the previously defined domain. Otherwise an exception is raised.

Execution Information

Parameters

RegionsRegionsRegionsRegionsregions (input_object)  region(-array) → objectHRegionHRegionHobject

Regions for which the fuzzy entropy is to be calculated.

ImageImageImageImageimage (input_object)  singlechannelimage → objectHImageHImageHobject (byte)

Input image containing the fuzzy membership values.

AparAparAparAparapar (input_control)  integer → HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Start of the fuzzy function.

Default value: 0

Suggested values: 0, 5, 10, 20, 50, 100

Typical range of values: 0 ≤ Apar Apar Apar Apar apar ≤ 255 (lin)

Minimum increment: 1

Recommended increment: 5

CparCparCparCparcpar (input_control)  integer → HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

End of the fuzzy function.

Default value: 255

Suggested values: 50, 100, 150, 200, 220, 255

Typical range of values: 0 ≤ Cpar Cpar Cpar Cpar cpar ≤ 255 (lin)

Minimum increment: 1

Recommended increment: 5

Restriction: Apar <= Cpar

EntropyEntropyEntropyEntropyentropy (output_control)  real(-array) → HTupleHTupleHtuple (real) (double) (double) (double)

Fuzzy entropy of a region.

Example (HDevelop)

* To find a Fuzzy Entropy from an Image
read_image(Image,'monkey')
fuzzy_entropy(Trans,Trans,0,255,Entro)

Example (C)

/* To find a Fuzzy Entropy from an Image */
read_image(&Image,'monkey') ;
fuzzy_entropy(Trans,Trans,0,255,&Entro) ;

Example (HDevelop)

* To find a Fuzzy Entropy from an Image
read_image(Image,'monkey')
fuzzy_entropy(Trans,Trans,0,255,Entro)

Example (HDevelop)

* To find a Fuzzy Entropy from an Image
read_image(Image,'monkey')
fuzzy_entropy(Trans,Trans,0,255,Entro)

Example (HDevelop)

* To find a Fuzzy Entropy from an Image
read_image(Image,'monkey')
fuzzy_entropy(Trans,Trans,0,255,Entro)

Result

The operator fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropyFuzzyEntropy returns the value 2 (H_MSG_TRUE) if the parameters are correct. Otherwise an exception is raised.

See also

fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeter

References

M.K. Kundu, S.K. Pal: “Automatic selection of object enhancement operator with quantitative justification based on fuzzy set theoretic measures”; Pattern Recognition Letters 11; 1990; pp. 811-829.

Module

Foundation

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HALCON Operator Reference 18.05 Copyright © 1996-2018 MVTec Software GmbH