points_harris_binomialPointsHarrisBinomialPointsHarrisBinomialpoints_harris_binomialT_points_harris_binomial🔗

Short description🔗

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

Signature🔗

points_harris_binomial( image Image, integer MaskSizeGrad, integer MaskSizeSmooth, real Alpha, number Threshold, string Subpix, out point.y Row, out point.x Column )

Description🔗

points_harrisPointsHarris extracts points of interest from an image Imageimageimage. The Harris operator is based upon the smoothed matrix

\[\begin{eqnarray*} M = G_{\sigma} * \left( \begin{array}{cc} \displaystyle I_{x}^{2} & \displaystyle I_{x}I_{y} \\ \displaystyle I_{x}I_{y} & \displaystyle I_{y}^{2} \end{array} \right) \enspace , \end{eqnarray*}\]

where \(G_{\sigma}\) stands for a Binomial smoothing of size MaskSizeSmoothmaskSizeSmoothmask_size_smooth and \(I_{x}\) and \(I_{y}\) are the first derivatives of the image, computed with a Sobel filter of size MaskSizeGradmaskSizeGradmask_size_grad. The resulting points are the positive local extrema of

\[\begin{eqnarray*} \mathrm{Det}M - \textrm{Alpha}*(\mathrm{Trace}M)^{2}. \end{eqnarray*}\]

If necessary, they can be restricted to points with a minimum filter response of Thresholdthresholdthreshold. By default the coordinates of the points are calculated with subpixel accuracy. This can be turned off by setting the parameter Subpixsubpixsubpix 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🔗

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🔗

Imageimageimage (input_object) (multichannel-)image → object (byte / uint2)HObject (byte / uint2)HImage (byte / uint2)HObject (byte / uint2)Hobject (byte / uint2)

Input image.

MaskSizeGradmaskSizeGradmask_size_grad (input_control) integer → (integer)HTuple (Hlong)HTuple (int / long)intHtuple (Hlong)

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

Default: 55
Suggested values: 3, 5, 7, 9, 11, 15, 21, 313, 5, 7, 9, 11, 15, 21, 31
Value range: 1 ≤ MaskSizeGrad
Recommended increment: 2

MaskSizeSmoothmaskSizeSmoothmask_size_smooth (input_control) integer → (integer)HTuple (Hlong)HTuple (int / long)intHtuple (Hlong)

Amount of smoothing used for the integration of the gradients.

Default: 1515
Suggested values: 3, 5, 7, 9, 11, 15, 21, 313, 5, 7, 9, 11, 15, 21, 31
Value range: 1 ≤ MaskSizeSmooth
Recommended increment: 2

Alphaalphaalpha (input_control) real → (real)HTuple (double)HTuple (double)floatHtuple (double)

Weight of the squared trace of the squared gradient matrix.

Default: 0.080.08
Suggested values: 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08
Value range: 0.0 ≤ Alpha
Minimum increment: 0.001
Recommended increment: 0.01

Thresholdthresholdthreshold (input_control) number → (real / integer)HTuple (double / Hlong)HTuple (double / int / long)Union[float, int]Htuple (double / Hlong)

Minimum filter response for the points.

Default: 1000.01000.0
Value range: 0.0 ≤ Threshold

Subpixsubpixsubpix (input_control) string → (string)HTuple (HString)HTuple (string)strHtuple (char*)

Turn on or off subpixel refinement.

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

Rowrowrow (output_control) point.y-array → (real)HTuple (double)HTuple (double)Sequence[float]Htuple (double)

Row coordinates of the detected points.

Columncolumncolumn (output_control) point.x-array → (real)HTuple (double)HTuple (double)Sequence[float]Htuple (double)

Column coordinates of the detected points.

Result🔗

points_harrisPointsHarris 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>). If necessary, an exception is raised.

Combinations with other operators🔗

Combinations

Possible successors

gen_cross_contour_xldGenCrossContourXld

Alternatives

points_foerstnerPointsFoerstner, points_harrisPointsHarris, points_lepetitPointsLepetit, points_sojkaPointsSojka

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