zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPix (Operator)
Name
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPix — Extract zero crossings from an image with subpixel accuracy.
Signature
Description
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPix extracts the zero crossings of the
input image ImageImageImageImageimage with subpixel accuracy. The extracted
zero crossings are returned as XLD-contours in
ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossings. Thus, zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPix can be
used as a sub-pixel precise edge extractor if the input image is a
Laplace-filtered image (see laplacelaplaceLaplaceLaplaceLaplace,
laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGauss, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGauss).
For the extraction, the input image is regarded as a surface, in
which the gray values are interpolated bilinearly between the
centers of the individual pixels. Consistent with the surface thus
defined, zero crossing lines are extracted for each pixel and linked
into topologically sound contours. This means that the zero
crossing contours are correctly split at junction points. If the
image contains extended areas of constant gray value 0, only the
border of such areas is returned as zero crossings.
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
ImageImageImageImageimage (input_object) singlechannelimage → objectHImageHImageHobject (int1 / int2 / int4 / real)
Input image.
ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossings (output_object) xld_cont-array → objectHXLDContHXLDContHobject *
Extracted zero crossings.
Example (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)
Example (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);
Example (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)
Example (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)
Example (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)
Result
zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPix usually returns the value 2 (H_MSG_TRUE). If
necessary, an exception is raised.
Possible Predecessors
laplacelaplaceLaplaceLaplaceLaplace,
laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGauss,
diff_of_gaussdiff_of_gaussDiffOfGaussDiffOfGaussDiffOfGauss,
derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGauss
Alternatives
zero_crossingzero_crossingZeroCrossingZeroCrossingZeroCrossing
See also
threshold_sub_pixthreshold_sub_pixThresholdSubPixThresholdSubPixThresholdSubPix
Module
2D Metrology