fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter (算子)

名称

fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter — 计算一个区域的模糊周长。

签名

fuzzy_perimeter(Regions, Image : : Apar, Cpar : Perimeter)

Herror fuzzy_perimeter(const Hobject Regions, const Hobject Image, const Hlong Apar, const Hlong Cpar, double* Perimeter)

Herror T_fuzzy_perimeter(const Hobject Regions, const Hobject Image, const Htuple Apar, const Htuple Cpar, Htuple* Perimeter)

void FuzzyPerimeter(const HObject& Regions, const HObject& Image, const HTuple& Apar, const HTuple& Cpar, HTuple* Perimeter)

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

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

static void HOperatorSet.FuzzyPerimeter(HObject regions, HObject image, HTuple apar, HTuple cpar, out HTuple perimeter)

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

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

def fuzzy_perimeter(regions: HObject, image: HObject, apar: int, cpar: int) -> Sequence[float]

def fuzzy_perimeter_s(regions: HObject, image: HObject, apar: int, cpar: int) -> float

描述

算子 fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter is used to determine the differences of fuzzy membership between an image point and its neighbor points. The right and lower neighbor are taken into account. The fuzzy perimeter is then defined as follows: where MxN is the size of the image, and u(x(m,n)) is the fuzzy membership function (i.e., the input image). This implementation uses Zadeh's Standard-S function, which is defined as follows: The parameters a, b and c obey the following restrictions: is the inflection point of the function, is the bandwidth, and for x = b holds. In fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter, the parameters AparAparAparAparaparapar and CparCparCparCparcparcpar are defined as follows: b is

注意

Note that for fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter, the RegionsRegionsRegionsRegionsregionsregions must lie completely within the previously defined domain.否则将抛出异常。

执行信息

参数

RegionsRegionsRegionsRegionsregionsregions (输入对象)  region(-array) objectHRegionHObjectHRegionHobject

Regions for which the fuzzy perimeter is to be calculated.

ImageImageImageImageimageimage (输入对象)  singlechannelimage objectHImageHObjectHImageHobject (byte)

Input image containing the fuzzy membership values.

AparAparAparAparaparapar (输入控制)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Start of the fuzzy function.

默认值: 0

建议值: 0, 5, 10, 20, 50, 100

值范围: 0 ≤ Apar Apar Apar Apar apar apar ≤ 255 (lin)

最小增量: 1

建议增量: 5

CparCparCparCparcparcpar (输入控制)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

End of the fuzzy function.

默认值: 255

建议值: 50, 100, 150, 200, 220, 255

值范围: 0 ≤ Cpar Cpar Cpar Cpar cpar cpar ≤ 255 (lin)

最小增量: 1

建议增量: 5

限制: Apar <= Cpar

PerimeterPerimeterPerimeterPerimeterperimeterperimeter (输出控制)  real(-array) HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Fuzzy perimeter of a region.

示例(HDevelop)

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

示例(C)

/* To find a Fuzzy Entropy from an Image */
read_image(&Image,"monkey");
fuzzy_perimeter(Trans,Trans,Apar,Bpar,&Per);

示例(HDevelop)

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

示例(HDevelop)

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

示例(HDevelop)

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

结果

算子 fuzzy_perimeterfuzzy_perimeterFuzzyPerimeterFuzzyPerimeterFuzzyPerimeterfuzzy_perimeter 在参数正确时返回值 2 ( H_MSG_TRUE )。否则将抛出异常。

另见

fuzzy_entropyfuzzy_entropyFuzzyEntropyFuzzyEntropyFuzzyEntropyfuzzy_entropy

参考文献

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.

模块

基础