ClassesClassesClassesClasses | | | | Operators

local_min_sub_pixT_local_min_sub_pixLocalMinSubPixlocal_min_sub_pixLocalMinSubPixLocalMinSubPix (Operator)

Name

local_min_sub_pixT_local_min_sub_pixLocalMinSubPixlocal_min_sub_pixLocalMinSubPixLocalMinSubPix — Subpixel precise detection of local minima in an image.

Signature

local_min_sub_pix(Image : : Filter, Sigma, Threshold : Row, Column)

Herror T_local_min_sub_pix(const Hobject Image, const Htuple Filter, const Htuple Sigma, const Htuple Threshold, Htuple* Row, Htuple* Column)

Herror local_min_sub_pix(Hobject Image, const HTuple& Filter, const HTuple& Sigma, const HTuple& Threshold, HTuple* Row, HTuple* Column)

HTuple HImage::LocalMinSubPix(const HTuple& Filter, const HTuple& Sigma, const HTuple& Threshold, HTuple* Column) const

void LocalMinSubPix(const HObject& Image, const HTuple& Filter, const HTuple& Sigma, const HTuple& Threshold, HTuple* Row, HTuple* Column)

void HImage::LocalMinSubPix(const HString& Filter, double Sigma, double Threshold, HTuple* Row, HTuple* Column) const

void HImage::LocalMinSubPix(const char* Filter, double Sigma, double Threshold, HTuple* Row, HTuple* Column) const

void HOperatorSetX.LocalMinSubPix(
[in] IHUntypedObjectX* Image, [in] VARIANT Filter, [in] VARIANT Sigma, [in] VARIANT Threshold, [out] VARIANT* Row, [out] VARIANT* Column)

VARIANT HImageX.LocalMinSubPix(
[in] BSTR Filter, [in] double Sigma, [in] double Threshold, [out] VARIANT* Column)

static void HOperatorSet.LocalMinSubPix(HObject image, HTuple filter, HTuple sigma, HTuple threshold, out HTuple row, out HTuple column)

void HImage.LocalMinSubPix(string filter, double sigma, double threshold, out HTuple row, out HTuple column)

Description

local_min_sub_pixlocal_min_sub_pixLocalMinSubPixlocal_min_sub_pixLocalMinSubPixLocalMinSubPix extracts local minima from the image ImageImageImageImageImageimage with subpixel precision. To do so, in each point the input image is approximated by a quadratic polynomial in x and y and subsequently the polynomial is examined for local minima. The partial derivatives, which are necessary for setting up the polynomial, are calculated either with various Gaussian derivatives or using the facet model, depending on FilterFilterFilterFilterFilterfilter. In the first case, SigmaSigmaSigmaSigmaSigmasigma determines the size of the Gaussian kernels, while in the second case, before being processed the input image is smoothed by a Gaussian whose size is determined by SigmaSigmaSigmaSigmaSigmasigma. Therefore, 'facet'"facet""facet""facet""facet""facet" results in a faster extraction at the expense of slightly less accurate results. A point is accepted to be a local minimum if both eigenvalues of the Hessian matrix are greater than ThresholdThresholdThresholdThresholdThresholdthreshold. The eigenvalues correspond to the curvature of the gray value surface.

Attention

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.

Parallelization

Parameters

ImageImageImageImageImageimage (input_object)  singlechannelimage objectHImageHImageHImageHImageXHobject (byte / int1 / int2 / uint2 / int4 / real)

Input image.

FilterFilterFilterFilterFilterfilter (input_control)  string HTupleHTupleHTupleVARIANTHtuple (string) (string) (HString) (char*) (BSTR) (char*)

Method for the calculation of the partial derivatives.

Default value: 'facet' "facet" "facet" "facet" "facet" "facet"

List of values: 'facet'"facet""facet""facet""facet""facet", 'gauss'"gauss""gauss""gauss""gauss""gauss"

SigmaSigmaSigmaSigmaSigmasigma (input_control)  real HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Sigma of the Gaussian. If FilterFilterFilterFilterFilterfilter is 'facet', SigmaSigmaSigmaSigmaSigmasigma may be 0.0 to avoid the smoothing of the input image.

Suggested values: 0.7, 0.8, 0.9, 1.0, 1.2, 1.5, 2.0, 3.0

Restriction: Sigma >= 0.0

ThresholdThresholdThresholdThresholdThresholdthreshold (input_control)  real HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Minimum absolute value of the eigenvalues of the Hessian matrix.

Default value: 5.0

Suggested values: 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0

Restriction: Threshold >= 0.0

RowRowRowRowRowrow (output_control)  point.y-array HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Row coordinates of the detected minima.

ColumnColumnColumnColumnColumncolumn (output_control)  point.x-array HTupleHTupleHTupleVARIANTHtuple (real) (double) (double) (double) (double) (double)

Column coordinates of the detected minima.

Result

local_min_sub_pixlocal_min_sub_pixLocalMinSubPixlocal_min_sub_pixLocalMinSubPixLocalMinSubPix returns 2 (H_MSG_TRUE) if all parameters are correct and no error occurs during the execution. 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.

Possible Successors

gen_cross_contour_xldgen_cross_contour_xldGenCrossContourXldgen_cross_contour_xldGenCrossContourXldGenCrossContourXld, disp_crossdisp_crossDispCrossdisp_crossDispCrossDispCross

Alternatives

critical_points_sub_pixcritical_points_sub_pixCriticalPointsSubPixcritical_points_sub_pixCriticalPointsSubPixCriticalPointsSubPix, local_max_sub_pixlocal_max_sub_pixLocalMaxSubPixlocal_max_sub_pixLocalMaxSubPixLocalMaxSubPix, saddle_points_sub_pixsaddle_points_sub_pixSaddlePointsSubPixsaddle_points_sub_pixSaddlePointsSubPixSaddlePointsSubPix

See also

local_minlocal_minLocalMinlocal_minLocalMinLocalMin, lowlandslowlandsLowlandslowlandsLowlandsLowlands, lowlands_centerlowlands_centerLowlandsCenterlowlands_centerLowlandsCenterLowlandsCenter

Module

Foundation


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