points_harris_binomialT_points_harris_binomialPointsHarrisBinomialPointsHarrisBinomialpoints_harris_binomial (Operator)

Name

points_harris_binomialT_points_harris_binomialPointsHarrisBinomialPointsHarrisBinomialpoints_harris_binomial — Detect points of interest using the binomial approximation of the Harris operator.

Signature

points_harris_binomial(Image : : MaskSizeGrad, MaskSizeSmooth, Alpha, Threshold, Subpix : Row, Column)

Description

points_harrispoints_harrisPointsHarrisPointsHarrispoints_harris extracts points of interest from an image ImageImageImageimageimage. The Harris operator is based upon the smoothed matrix where stands for a Binomial smoothing of size MaskSizeSmoothMaskSizeSmoothMaskSizeSmoothmaskSizeSmoothmask_size_smooth and and are the first derivatives of the image, computed with a Sobel filter of size MaskSizeGradMaskSizeGradMaskSizeGradmaskSizeGradmask_size_grad. The resulting points are the positive local extrema of If necessary, they can be restricted to points with a minimum filter response of ThresholdThresholdThresholdthresholdthreshold. By default the coordinates of the points are calculated with subpixel accuracy. This can be turned off by setting the parameter SubpixSubpixSubpixsubpixsubpix to 'off'.

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.

Execution Information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: global (may be called from any thread).
Automatically parallelized on internal data level.

Parameters

ImageImageImageimageimage (input_object) (multichannel-)image → object (byte / uint2)

Input image.

MaskSizeGradMaskSizeGradMaskSizeGradmaskSizeGradmask_size_grad (input_control) integer → (integer)

Amount of binomial smoothing used for the calculation of the gradient.

Default: 5

Suggested values: 3, 5, 7, 9, 11, 15, 21, 31

Value range: 1 ≤ MaskSizeGrad MaskSizeGrad MaskSizeGrad maskSizeGrad mask_size_grad

Recommended increment: 2

MaskSizeSmoothMaskSizeSmoothMaskSizeSmoothmaskSizeSmoothmask_size_smooth (input_control) integer → (integer)

Amount of smoothing used for the integration of the gradients.

Default: 15

Suggested values: 3, 5, 7, 9, 11, 15, 21, 31

Value range: 1 ≤ MaskSizeSmooth MaskSizeSmooth MaskSizeSmooth maskSizeSmooth mask_size_smooth

Recommended increment: 2

AlphaAlphaAlphaalphaalpha (input_control) real → (real)

Weight of the squared trace of the squared gradient matrix.

Default: 0.08

Suggested values: 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08

Value range: 0.0 ≤ Alpha Alpha Alpha alpha alpha

Minimum increment: 0.001

Recommended increment: 0.01

ThresholdThresholdThresholdthresholdthreshold (input_control) number → (real / integer)

Minimum filter response for the points.

Default: 1000.0

Value range: 0.0 ≤ Threshold Threshold Threshold threshold threshold

SubpixSubpixSubpixsubpixsubpix (input_control) string → (string)

Turn on or off subpixel refinement.

Default: 'on' "on" "on" "on" "on"

List of values: 'off'"off""off""off""off", 'on'"on""on""on""on"

RowRowRowrowrow (output_control) point.y-array → (real)

Row coordinates of the detected points.

ColumnColumnColumncolumncolumn (output_control) point.x-array → (real)

Column coordinates of the detected points.

Result

points_harrispoints_harrisPointsHarrisPointsHarrispoints_harris 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>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>). If necessary, an exception is raised.

Possible Successors

gen_cross_contour_xldgen_cross_contour_xldGenCrossContourXldGenCrossContourXldgen_cross_contour_xld

Alternatives

points_foerstnerpoints_foerstnerPointsFoerstnerPointsFoerstnerpoints_foerstner, points_harrispoints_harrisPointsHarrisPointsHarrispoints_harris, points_lepetitpoints_lepetitPointsLepetitPointsLepetitpoints_lepetit, points_sojkapoints_sojkaPointsSojkaPointsSojkapoints_sojka

References

C. Harris, M. Stephens: “A combined corner and edge detector”. Proceedings of the 4th Alvey Vision Conference, pp. 147-151, 1988.
V. Gouet, N.Boujemaa: “Object-based queries using color points of interest”. IEEE Workshop on Content-Based Access of Image and Video Libraries, CVPR/CBAIVL 2001, Hawaii, USA, 2001.

Module

Foundation

Operators