hamming_distance_normhamming_distance_normHammingDistanceNormHammingDistanceNormhamming_distance_norm (Operator)

名称

hamming_distance_normhamming_distance_normHammingDistanceNormHammingDistanceNormhamming_distance_norm — Hamming distance between two regions using normalization.

签名

hamming_distance_norm(Regions1, Regions2 : : Norm : Distance, Similarity)

Herror hamming_distance_norm(const Hobject Regions1, const Hobject Regions2, const char* Norm, Hlong* Distance, double* Similarity)

Herror T_hamming_distance_norm(const Hobject Regions1, const Hobject Regions2, const Htuple Norm, Htuple* Distance, Htuple* Similarity)

void HammingDistanceNorm(const HObject& Regions1, const HObject& Regions2, const HTuple& Norm, HTuple* Distance, HTuple* Similarity)

HTuple HRegion::HammingDistanceNorm(const HRegion& Regions2, const HTuple& Norm, HTuple* Similarity) const

Hlong HRegion::HammingDistanceNorm(const HRegion& Regions2, const HString& Norm, double* Similarity) const

Hlong HRegion::HammingDistanceNorm(const HRegion& Regions2, const char* Norm, double* Similarity) const

Hlong HRegion::HammingDistanceNorm(const HRegion& Regions2, const wchar_t* Norm, double* Similarity) const   ( Windows only)

static void HOperatorSet.HammingDistanceNorm(HObject regions1, HObject regions2, HTuple norm, out HTuple distance, out HTuple similarity)

HTuple HRegion.HammingDistanceNorm(HRegion regions2, HTuple norm, out HTuple similarity)

int HRegion.HammingDistanceNorm(HRegion regions2, string norm, out double similarity)

def hamming_distance_norm(regions_1: HObject, regions_2: HObject, norm: MaybeSequence[str]) -> Tuple[Sequence[int], Sequence[float]]

def hamming_distance_norm_s(regions_1: HObject, regions_2: HObject, norm: MaybeSequence[str]) -> Tuple[int, float]

描述

The operator hamming_distance_normhamming_distance_normHammingDistanceNormHammingDistanceNormHammingDistanceNormhamming_distance_norm returns the hamming distance between two regions, i.e., the number of pixels of the regions which are different (DistanceDistanceDistanceDistancedistancedistance). Before calculating the difference the region in Regions1Regions1Regions1Regions1regions1regions_1 is normalized onto the regions in Regions2Regions2Regions2Regions2regions2regions_2. The result is the number of pixels contained in one region but not in the other: The parameter SimilaritySimilaritySimilaritySimilaritysimilaritysimilarity describes the similarity between the two regions based on the hamming distance DistanceDistanceDistanceDistancedistancedistance:

The following types of normalization are available:

'center'"center""center""center""center""center":

The region is moved so that both regions have the save center of gravity.

If both regions are empty SimilaritySimilaritySimilaritySimilaritysimilaritysimilarity is set to 0. The regions with the same index from both input parameters are always compared.

注意

In both input parameters the same number of regions must be passed.

执行信息

参数

Regions1Regions1Regions1Regions1regions1regions_1 (input_object)  region(-array) objectHRegionHObjectHRegionHobject

Regions to be examined.

Regions2Regions2Regions2Regions2regions2regions_2 (input_object)  region(-array) objectHRegionHObjectHRegionHobject

Comparative regions.

NormNormNormNormnormnorm (input_control)  string(-array) HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Type of normalization.

默认值: 'center' "center" "center" "center" "center" "center"

值列表: 'center'"center""center""center""center""center"

DistanceDistanceDistanceDistancedistancedistance (output_control)  integer(-array) HTupleSequence[int]HTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Hamming distance of two regions.

Assertion: Distance >= 0

SimilaritySimilaritySimilaritySimilaritysimilaritysimilarity (output_control)  real(-array) HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Similarity of two regions.

Assertion: 0 <= Similarity && Similarity <= 1

Complexity

If F is the area of a region the mean runtime complexity is O(sqrt(F)).

结果

hamming_distance_norm returns the value 2 ( H_MSG_TRUE) if the number of objects in both parameters is the same and is not 0. The behavior in case of empty input (no input objects available) is set via the operator set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>). The behavior in case of empty region (the region is the empty set) is set via set_system('empty_region_result',<Result>)set_system("empty_region_result",<Result>)SetSystem("empty_region_result",<Result>)SetSystem("empty_region_result",<Result>)SetSystem("empty_region_result",<Result>)set_system("empty_region_result",<Result>). If necessary an exception is raised.

可能的前置算子

thresholdthresholdThresholdThresholdThresholdthreshold, regiongrowingregiongrowingRegiongrowingRegiongrowingRegiongrowingregiongrowing, connectionconnectionConnectionConnectionConnectionconnection

替代算子

intersectionintersectionIntersectionIntersectionIntersectionintersection, complementcomplementComplementComplementComplementcomplement, area_centerarea_centerAreaCenterAreaCenterAreaCenterarea_center

另见

hamming_change_regionhamming_change_regionHammingChangeRegionHammingChangeRegionHammingChangeRegionhamming_change_region

模块

Foundation