zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix (Operator)
Name
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix — Subpixel-genaues Extrahieren von Nulldurchgängen in einem Bild
Signatur
def zero_crossing_sub_pix(image: HObject) -> HObject
Beschreibung
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix extrahiert die Nulldurchgänge des
Eingabebildes ImageImageImageImageimageimage subpixel-genau. Die extrahierten
Nulldurchgänge werden als XLD-Konturen in ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossingszero_crossings
zurückgegeben. zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix kann somit zur
subpixel-genauen Kantenextraktion verwendet werden, wenn als
Eingabebild ein Laplace-gefiltertes Bild übergeben wird (siehe
laplacelaplaceLaplaceLaplaceLaplacelaplace, laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss).
Bei der Extraktion wird das Eingabebild als Oberfläche
interpretiert, wobei zwischen den Pixelmittelpunkten bilinear
interpoliert wird. Konsistent mit der so entstehenden Oberfläche
werden einzelne Nulldurchgangslinien für jedes Pixel extrahiert und
zu topologisch „sauberen“ Konturen verknüpft. Das
bedeutet, dass die Nulldurchgangskonturen an Kreuzungspunkten sauber
aufgetrennt werden. Falls im Bild flächenhafte Bereiche mit einem
konstanten Grauwert von 0 auftreten, wird nur der Rand solcher
Gebiete als Nulldurchgang zurückgeliefert.
Ausführungsinformationen
- Multithreading-Typ: reentrant (läuft parallel zu nicht-exklusiven Operatoren).
- Multithreading-Bereich: global (kann von jedem Thread aufgerufen werden).
- Wird ohne Parallelisierung verarbeitet.
Parameter
ImageImageImageImageimageimage (input_object) singlechannelimage → objectHImageHObjectHImageHobject (int1 / int2 / int4 / real)
Eingabebild.
ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossingszero_crossings (output_object) xld_cont-array → objectHXLDContHObjectHXLDContHobject *
Extrahierte Nulldurchgänge.
Beispiel (HDevelop)
* Detection zero crossings of the Laplacian-of-Gaussian
* of an aerial image
read_image(Image,'mreut')
derivate_gauss(Image,Laplace,3,'laplace')
zero_crossing_sub_pix(Laplace,ZeroCrossings)
dev_display(ZeroCrossings)
* Detection of edges, i.e, zero crossings of the Laplacian-of-Gaussian
* that have a large gradient magnitude, in an aerial image
read_image(Image,'mreut')
Sigma := 1.5
* Compensate the threshold for the fact that derivate_gauss(...,'gradient')
* calculates a Gaussian-smoothed gradient, in which the edge amplitudes
* are too small because of the Gaussian smoothing, to correspond to a true
* edge amplitude of 20.
Threshold := 20/(Sigma*sqrt(2*3.1415926))
derivate_gauss(Image,Gradient,Sigma,'gradient')
threshold(Gradient,Region,Threshold,255)
reduce_domain(Image,Region,ImageReduced)
derivate_gauss(ImageReduced,Laplace,Sigma,'laplace')
zero_crossing_sub_pix(Laplace,Edges)
dev_display(Edges)
Beispiel (C)
/* Detection zero crossings of the Laplacian-of-Gaussian of aerial image */
read_image(&Image,"mreut");
derivate_gauss(Image,&Laplace,3,"laplace");
zero_crossing_sub_pix(Laplace,&ZeroCrossings);
disp_xld(ZeroCrossings,WindowHandle);
/* Detection of edges, i.e, zero crossings of the Laplacian-of-Gaussian
that have a large gradient magnitude, in an aerial image */
read_image(&Image,"mreut");
Sigma = 1.5;
/* Compensate the threshold for the fact that derivate_gauss(...,'gradient')
calculates a Gaussian-smoothed gradient, in which the edge amplitudes
are too small because of the Gaussian smoothing, to correspond to a true
edge amplitude of 20. */
Threshold = 20/(Sigma*sqrt(2*PI));
derivate_gauss(Image,&Gradient,Sigma,"gradient");
threshold(Gradient,&Region,Threshold,255);
reduce_domain(Image,Region,&ImageReduced);
derivate_gauss(ImageReduced,&Laplace,Sigma,"laplace");
zero_crossing_sub_pix(Laplace,&Edges);
disp_xld(Edges,WindowHandle);
Beispiel (HDevelop)
* Detection zero crossings of the Laplacian-of-Gaussian
* of an aerial image
read_image(Image,'mreut')
derivate_gauss(Image,Laplace,3,'laplace')
zero_crossing_sub_pix(Laplace,ZeroCrossings)
dev_display(ZeroCrossings)
* Detection of edges, i.e, zero crossings of the Laplacian-of-Gaussian
* that have a large gradient magnitude, in an aerial image
read_image(Image,'mreut')
Sigma := 1.5
* Compensate the threshold for the fact that derivate_gauss(...,'gradient')
* calculates a Gaussian-smoothed gradient, in which the edge amplitudes
* are too small because of the Gaussian smoothing, to correspond to a true
* edge amplitude of 20.
Threshold := 20/(Sigma*sqrt(2*3.1415926))
derivate_gauss(Image,Gradient,Sigma,'gradient')
threshold(Gradient,Region,Threshold,255)
reduce_domain(Image,Region,ImageReduced)
derivate_gauss(ImageReduced,Laplace,Sigma,'laplace')
zero_crossing_sub_pix(Laplace,Edges)
dev_display(Edges)
Beispiel (HDevelop)
* Detection zero crossings of the Laplacian-of-Gaussian
* of an aerial image
read_image(Image,'mreut')
derivate_gauss(Image,Laplace,3,'laplace')
zero_crossing_sub_pix(Laplace,ZeroCrossings)
dev_display(ZeroCrossings)
* Detection of edges, i.e, zero crossings of the Laplacian-of-Gaussian
* that have a large gradient magnitude, in an aerial image
read_image(Image,'mreut')
Sigma := 1.5
* Compensate the threshold for the fact that derivate_gauss(...,'gradient')
* calculates a Gaussian-smoothed gradient, in which the edge amplitudes
* are too small because of the Gaussian smoothing, to correspond to a true
* edge amplitude of 20.
Threshold := 20/(Sigma*sqrt(2*3.1415926))
derivate_gauss(Image,Gradient,Sigma,'gradient')
threshold(Gradient,Region,Threshold,255)
reduce_domain(Image,Region,ImageReduced)
derivate_gauss(ImageReduced,Laplace,Sigma,'laplace')
zero_crossing_sub_pix(Laplace,Edges)
dev_display(Edges)
Beispiel (HDevelop)
* Detection zero crossings of the Laplacian-of-Gaussian
* of an aerial image
read_image(Image,'mreut')
derivate_gauss(Image,Laplace,3,'laplace')
zero_crossing_sub_pix(Laplace,ZeroCrossings)
dev_display(ZeroCrossings)
* Detection of edges, i.e, zero crossings of the Laplacian-of-Gaussian
* that have a large gradient magnitude, in an aerial image
read_image(Image,'mreut')
Sigma := 1.5
* Compensate the threshold for the fact that derivate_gauss(...,'gradient')
* calculates a Gaussian-smoothed gradient, in which the edge amplitudes
* are too small because of the Gaussian smoothing, to correspond to a true
* edge amplitude of 20.
Threshold := 20/(Sigma*sqrt(2*3.1415926))
derivate_gauss(Image,Gradient,Sigma,'gradient')
threshold(Gradient,Region,Threshold,255)
reduce_domain(Image,Region,ImageReduced)
derivate_gauss(ImageReduced,Laplace,Sigma,'laplace')
zero_crossing_sub_pix(Laplace,Edges)
dev_display(Edges)
Ergebnis
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix liefert normalerweise den Wert TRUE.
Gegebenenfalls wird eine Fehlerbehandlung durchgeführt.
Vorgänger
laplacelaplaceLaplaceLaplaceLaplacelaplace,
laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss,
diff_of_gaussdiff_of_gaussDiffOfGaussDiffOfGaussDiffOfGaussdiff_of_gauss,
derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss
Alternativen
zero_crossingzero_crossingZeroCrossingZeroCrossingZeroCrossingzero_crossing
Siehe auch
threshold_sub_pixthreshold_sub_pixThresholdSubPixThresholdSubPixThresholdSubPixthreshold_sub_pix
Modul
2D Metrology