Operator Reference

HALCON Operator Reference / Filters / Smoothing
ClassesClasses | | Operators

gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter (Operator)

gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter — Smooth using discrete Gauss functions.

Signature

gauss_filter(Image : ImageGauss : Size : )

Herror gauss_filter(const Hobject Image, Hobject* ImageGauss, const Hlong Size)

Herror T_gauss_filter(const Hobject Image, Hobject* ImageGauss, const Htuple Size)

void GaussFilter(const HObject& Image, HObject* ImageGauss, const HTuple& Size)

HImage HImage::GaussFilter(Hlong Size) const

static void HOperatorSet.GaussFilter(HObject image, out HObject imageGauss, HTuple size)

HImage HImage.GaussFilter(int size)

def gauss_filter(image: HObject, size: int) -> HObject

Description

The operator gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter smoothes images using the discrete Gaussian, a discrete approximation of the Gaussian function,

The smoothing effect increases with increasing filter size. The following filter sizes (SizeSizeSizesizesize) are supported (the sigma value of the Gauss function is indicated in brackets):

  • 3 (0.600)

  • 5 (1.075)

  • 7 (1.550)

  • 9 (2.025)

  • 11 (2.550)

For border treatment the gray values of the images are reflected at the image borders. Notice that, contrary to the operator gauss_imagegauss_imageGaussImageGaussImagegauss_image, the relationship between the filter mask size and its respective value for the sigma parameter is linear.

The operator binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter can be used as an alternative to gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter. binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter is significantly faster than gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter. It should be noted that the mask size in binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter does not lead to the same amount of smoothing as the mask size in gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter. Corresponding mask sizes can be determined based on the respective values of the Gaussian smoothing parameter sigma.

gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter can be executed on OpenCL devices for all supported image types. However, the OpenCL implementation can produce slightly different results from the scalar implementation.

For an explanation of the concept of smoothing filters see the introduction of chapter Filters / Smoothing.

Attention

In order to be able to process gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter on an OpenCL device, ImageImageImageimageimage must be at least 64 pixels in both width and height.

Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.

Execution Information

  • Supports OpenCL compute devices.
  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).
  • Multithreading scope: global (may be called from any thread).
  • Automatically parallelized on tuple level.
  • Automatically parallelized on channel level.
  • Automatically parallelized on domain level.

Parameters

ImageImageImageimageimage (input_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject (byte* / int2* / uint2* / int4* / real*) *allowed for compute devices

Image to be smoothed.

ImageGaussImageGaussImageGaussimageGaussimage_gauss (output_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject * (byte / int2 / uint2 / int4 / real)

Filtered image.

SizeSizeSizesizesize (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Required filter size.

Default: 5

List of values: 3, 5, 7, 9, 11

Example (HDevelop)

gauss_filter(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

Example (C)

gauss_filter(Input,&Gauss,7,);
regiongrowing(Gauss,&Segments,7,7,5,100,);

Example (HDevelop)

gauss_filter(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

Example (HDevelop)

gauss_filter(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

Complexity

For each pixel: O(Size * 2).

Result

If the parameter values are correct the operator gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter returns the value 2 ( H_MSG_TRUE) . The behavior in case of empty input (no input images 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>)set_system("no_object_result",<Result>). If necessary an exception is raised.

Possible Predecessors

read_imageread_imageReadImageReadImageread_image, grab_imagegrab_imageGrabImageGrabImagegrab_image

Possible Successors

regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing, thresholdthresholdThresholdThresholdthreshold, sub_imagesub_imageSubImageSubImagesub_image, dyn_thresholddyn_thresholdDynThresholdDynThresholddyn_threshold, auto_thresholdauto_thresholdAutoThresholdAutoThresholdauto_threshold

Alternatives

binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image, derivate_gaussderivate_gaussDerivateGaussDerivateGaussderivate_gauss, isotropic_diffusionisotropic_diffusionIsotropicDiffusionIsotropicDiffusionisotropic_diffusion

See also

mean_imagemean_imageMeanImageMeanImagemean_image, anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion, sigma_imagesigma_imageSigmaImageSigmaImagesigma_image, gen_lowpassgen_lowpassGenLowpassGenLowpassgen_lowpass

Module

Foundation

ClassesClasses | | Operators