zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix (算子)

名称

zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix — 以亚像素精度从图像中提取零交叉点。

签名

zero_crossing_sub_pix(Image : ZeroCrossings : : )

描述

zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix extracts the zero crossings of the input image ImageImageImageImageimageimage with subpixel accuracy. The extracted zero crossings are returned as XLD-contours in ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossingszero_crossings. Thus, zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix can be used as a sub-pixel precise edge extractor if the input image is a Laplace-filtered image (see laplacelaplaceLaplaceLaplaceLaplacelaplace, laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss).

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.

执行信息

多线程类型：可重入（与非独占算子并行运行）。
多线程作用域：全局（可从任何线程调用）。
未采用并行化处理。

参数

ImageImageImageImageimageimage (输入对象) singlechannelimage → object (int1 / int2 / int4 / real)

输入图像。

ZeroCrossingsZeroCrossingsZeroCrossingsZeroCrossingszeroCrossingszero_crossings (输出对象) xld_cont-array → object

Extracted zero crossings.

示例（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)

示例（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);

示例（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)

示例（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)

示例（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)

结果

zero_crossing_sub_pixzero_crossing_sub_pixZeroCrossingSubPixZeroCrossingSubPixZeroCrossingSubPixzero_crossing_sub_pix usually returns the value 2 ( H_MSG_TRUE) 。如有必要，则抛出异常。

可能的前趋

laplacelaplaceLaplaceLaplaceLaplacelaplace, laplace_of_gausslaplace_of_gaussLaplaceOfGaussLaplaceOfGaussLaplaceOfGausslaplace_of_gauss, diff_of_gaussdiff_of_gaussDiffOfGaussDiffOfGaussDiffOfGaussdiff_of_gauss, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss

替代

zero_crossingzero_crossingZeroCrossingZeroCrossingZeroCrossingzero_crossing

另见

threshold_sub_pixthreshold_sub_pixThresholdSubPixThresholdSubPixThresholdSubPixthreshold_sub_pix

模块

二维计量

算子