Name
diff_of_gaussdiff_of_gaussDiffOfGaussdiff_of_gaussDiffOfGaussDiffOfGauss — Approximate the LoG operator (Laplace of Gaussian).
diff_of_gaussdiff_of_gaussDiffOfGaussdiff_of_gaussDiffOfGaussDiffOfGauss approximates the Laplace-of-Gauss
operator by a difference of Gaussians. The standard deviations of
these Gaussians can be calculated, according to Marr, from the
Parameter SigmaSigmaSigmaSigmaSigmasigma of the LoG and the ratio of the two
standard deviations (SigFactorSigFactorSigFactorSigFactorSigFactorsigFactor) as:
For a SigFactor = 1.6, according
to Marr, an approximation to the Mexican-Hat-Operator results. The
resulting image is stored in DiffOfGaussDiffOfGaussDiffOfGaussDiffOfGaussDiffOfGaussdiffOfGauss.
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.
- 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.
Smoothing parameter of the Laplace operator to
approximate.
Default value: 3.0
Suggested values: 2.0, 3.0, 4.0, 5.0
Typical range of values: 0.2
≤
Sigma
Sigma
Sigma
Sigma
Sigma
sigma
≤
50.0
Minimum increment: 0.01
Recommended increment: 0.1
Restriction: Sigma > 0.0
Ratio of the standard deviations used (Marr
recommends 1.6).
Default value: 1.6
Typical range of values: 0.1
≤
SigFactor
SigFactor
SigFactor
SigFactor
SigFactor
sigFactor
≤
10.0
Minimum increment: 0.01
Recommended increment: 0.1
Restriction: SigFactor > 0.0
read_image(Image,'fabrik')
diff_of_gauss(Image,Laplace,2.0,1.6)
zero_crossing(Laplace,ZeroCrossings)
read_image(&Image,"mreut");
diff_of_gauss(Image,&Laplace,2.0,1.6);
zero_crossing(Laplace,&ZeroCrossings);
read_image(Image,'fabrik')
diff_of_gauss(Image,Laplace,2.0,1.6)
zero_crossing(Laplace,ZeroCrossings)
read_image(Image,'fabrik')
diff_of_gauss(Image,Laplace,2.0,1.6)
zero_crossing(Laplace,ZeroCrossings)
read_image(Image,'fabrik')
diff_of_gauss(Image,Laplace,2.0,1.6)
zero_crossing(Laplace,ZeroCrossings)
read_image(Image,'fabrik')
diff_of_gauss(Image,Laplace,2.0,1.6)
zero_crossing(Laplace,ZeroCrossings)
The execution time depends linearly on the number of pixels and the
size of sigma.
diff_of_gaussdiff_of_gaussDiffOfGaussdiff_of_gaussDiffOfGaussDiffOfGauss returns 2 (H_MSG_TRUE) if all parameters are
correct. If the input is empty the behavior can be set via
set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>). If
necessary, an exception is raised.
zero_crossingzero_crossingZeroCrossingzero_crossingZeroCrossingZeroCrossing,
dual_thresholddual_thresholdDualThresholddual_thresholdDualThresholdDualThreshold
laplacelaplaceLaplacelaplaceLaplaceLaplace,
derivate_gaussderivate_gaussDerivateGaussderivate_gaussDerivateGaussDerivateGauss
D. Marr: “Vision (A computational investigation into human
representation and processing of visual information)”; New York,
W.H. Freeman and Company; 1982.
Foundation