points_sojkaT_points_sojkaPointsSojkaPointsSojkapoints_sojka (Operator)

Name

points_sojkaT_points_sojkaPointsSojkaPointsSojkapoints_sojka — Find corners using the Sojka operator.

Signature

points_sojka(Image : : MaskSize, SigmaW, SigmaD, MinGrad, MinApparentness, MinAngle, Subpix : Row, Column)

Herror T_points_sojka(const Hobject Image, const Htuple MaskSize, const Htuple SigmaW, const Htuple SigmaD, const Htuple MinGrad, const Htuple MinApparentness, const Htuple MinAngle, const Htuple Subpix, Htuple* Row, Htuple* Column)

void PointsSojka(const HObject& Image, const HTuple& MaskSize, const HTuple& SigmaW, const HTuple& SigmaD, const HTuple& MinGrad, const HTuple& MinApparentness, const HTuple& MinAngle, const HTuple& Subpix, HTuple* Row, HTuple* Column)

void HImage::PointsSojka(Hlong MaskSize, const HTuple& SigmaW, const HTuple& SigmaD, const HTuple& MinGrad, const HTuple& MinApparentness, double MinAngle, const HString& Subpix, HTuple* Row, HTuple* Column) const

void HImage::PointsSojka(Hlong MaskSize, double SigmaW, double SigmaD, double MinGrad, double MinApparentness, double MinAngle, const HString& Subpix, HTuple* Row, HTuple* Column) const

void HImage::PointsSojka(Hlong MaskSize, double SigmaW, double SigmaD, double MinGrad, double MinApparentness, double MinAngle, const char* Subpix, HTuple* Row, HTuple* Column) const

void HImage::PointsSojka(Hlong MaskSize, double SigmaW, double SigmaD, double MinGrad, double MinApparentness, double MinAngle, const wchar_t* Subpix, HTuple* Row, HTuple* Column) const   ( Windows only)

static void HOperatorSet.PointsSojka(HObject image, HTuple maskSize, HTuple sigmaW, HTuple sigmaD, HTuple minGrad, HTuple minApparentness, HTuple minAngle, HTuple subpix, out HTuple row, out HTuple column)

void HImage.PointsSojka(int maskSize, HTuple sigmaW, HTuple sigmaD, HTuple minGrad, HTuple minApparentness, double minAngle, string subpix, out HTuple row, out HTuple column)

void HImage.PointsSojka(int maskSize, double sigmaW, double sigmaD, double minGrad, double minApparentness, double minAngle, string subpix, out HTuple row, out HTuple column)

def points_sojka(image: HObject, mask_size: int, sigma_w: Union[float, int], sigma_d: Union[float, int], min_grad: Union[int, float], min_apparentness: Union[int, float], min_angle: float, subpix: str) -> Tuple[Sequence[float], Sequence[float]]

Description

points_sojkapoints_sojkaPointsSojkaPointsSojkapoints_sojka defines a corner as the point of intersection of two straight, non-collinear gray value edges. To decide whether a point of the input image ImageImageImageimageimage is a corner or not, a neighborhood of MaskSizeMaskSizeMaskSizemaskSizemask_size x MaskSizeMaskSizeMaskSizemaskSizemask_size points is inspected. Only those image regions that are relevant for the decision are considered. Pixels with a magnitude of the gradient of less than MinGradMinGradMinGradminGradmin_grad are ignored from the outset.

Furthermore, only those of the remaining points are used that belong to one of the two gray value edges that form the corner. For this, the so called Apparentness is calculated, which is an indicator of the probability that the examined point actually is a corner point. Essentially, it is determined by the number of relevant points and their gradients. A point can only be accepted as a corner when its Apparentness is at least MinApparentnessMinApparentnessMinApparentnessminApparentnessmin_apparentness. Typical values of MinApparentnessMinApparentnessMinApparentnessminApparentnessmin_apparentness should range in the region of a few multiples of MinGradMinGradMinGradminGradmin_grad.

To calculate the Apparentness, each mask point is weighted according to two criteria: First, the influence of a mask point is weighted with a Gaussian of size SigmaWSigmaWSigmaWsigmaWsigma_w according to its distance from the possible corner point. SigmaWSigmaWSigmaWsigmaWsigma_w should be roughly between quarter and half of MaskSizeMaskSizeMaskSizemaskSizemask_size to obtain a reasonable proportion of the size of the weighting function to the mask size. Secondly, the distance of the point from the (assumed) ideal gray value edge is estimated and the point is weighted with a Gaussian of size SigmaDSigmaDSigmaDsigmaDsigma_d according to that distance. I.e., pixels that (due to the discretization of the input image) lie farther from the ideal gray value edge have less influence on the result than pixels with a smaller distance. Typically, it is not necessary to modify the default value 0.75 of SigmaDSigmaDSigmaDsigmaDsigma_d .

As a further criterion, the angle is calculated, by which the gray value edges change their direction in the corner point. A point can only be accepted as a corner when this angle is greater than MinAngleMinAngleMinAngleminAnglemin_angle.

The position of the detected corner points is returned in (RowRowRowrowrow, ColumnColumnColumncolumncolumn). RowRowRowrowrow and ColumnColumnColumncolumncolumn are calculated with subpixel accuracy if SubpixSubpixSubpixsubpixsubpix is 'true'"true""true""true""true". They are calculated only with pixel accuracy if SubpixSubpixSubpixsubpixsubpix is 'false'"false""false""false""false".

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

Parameters

ImageImageImageimageimage (input_object)  singlechannelimage objectHImageHObjectHObjectHobject (byte / int1 / int2 / uint2 / int4 / real)

Input image.

MaskSizeMaskSizeMaskSizemaskSizemask_size (input_control)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Required filter size.

Default: 9

List of values: 5, 7, 9, 11, 13

SigmaWSigmaWSigmaWsigmaWsigma_w (input_control)  number HTupleUnion[float, int]HTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Sigma of the weight function according to the distance to the corner candidate.

Default: 2.5

Suggested values: 2.0, 2.2, 2.4, 2.5, 2.6, 2.8, 3.0

Restriction: 2.0 <= SigmaW && SigmaW <= 3.0

SigmaDSigmaDSigmaDsigmaDsigma_d (input_control)  number HTupleUnion[float, int]HTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Sigma of the weight function for the distance to the ideal gray value edge.

Default: 0.75

Suggested values: 0.6, 0.7, 0.75, 0.8, 0.9, 1.0

Restriction: 0.6 <= SigmaD && SigmaD <= 1.0

MinGradMinGradMinGradminGradmin_grad (input_control)  number HTupleUnion[int, float]HTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Threshold for the magnitude of the gradient.

Default: 30.0

Suggested values: 20.0, 15.0, 30.0, 35.0, 40.0

MinApparentnessMinApparentnessMinApparentnessminApparentnessmin_apparentness (input_control)  number HTupleUnion[int, float]HTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Threshold for Apparentness.

Default: 90.0

Suggested values: 30.0, 60.0, 90.0, 150.0, 300.0, 600.0, 1500.0

MinAngleMinAngleMinAngleminAnglemin_angle (input_control)  angle.rad HTuplefloatHTupleHtuple (real) (double) (double) (double)

Threshold for the direction change in a corner point (radians).

Default: 0.5

Restriction: 0.0 <= MinAngle && MinAngle <= pi

SubpixSubpixSubpixsubpixsubpix (input_control)  string HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Subpixel precise calculation of the corner points.

Default: 'false' "false" "false" "false" "false"

List of values: 'false'"false""false""false""false", 'true'"true""true""true""true"

RowRowRowrowrow (output_control)  point.y-array HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Row coordinates of the detected corner points.

ColumnColumnColumncolumncolumn (output_control)  point.x-array HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Column coordinates of the detected corner points.

Result

points_sojkapoints_sojkaPointsSojkaPointsSojkapoints_sojka 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.

References

Eduard Sojka: “A New and Efficient Algorithm for Detecting the Corners in Digital Images”. Pattern Recognition, Luc Van Gool (Editor), LNCS 2449, pp. 125-132, Springer Verlag, 2002.

Module

Foundation