points_sojka🔗
Short description🔗
points_sojka — Find corners using the Sojka operator.
Signature🔗
points_sojka( image Image, integer MaskSize, number SigmaW, number SigmaD, number MinGrad, number MinApparentness, angle.rad MinAngle, string Subpix, out point.y Row, out point.x Column )
Description🔗
points_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 Image is a corner or not, a neighborhood of
MaskSize x
MaskSize 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 MinGrad 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
MinApparentness. Typical values of MinApparentness should
range in the region of a few multiples of MinGrad.
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
SigmaW according to its distance from the possible corner point.
SigmaW should be roughly between quarter and half of
MaskSize 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
SigmaD 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 SigmaD .
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
MinAngle.
The position of the detected corner points is returned in
(Row, Column). Row and Column are calculated
with subpixel accuracy if Subpix is 'true'. They are
calculated only with pixel accuracy if Subpix is
'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🔗
Execution information
-
Multithreading type: reentrant (runs in parallel with non-exclusive operators).
-
Multithreading scope: global (may be called from any thread).
-
Processed without parallelization.
Parameters🔗
Image (input_object) singlechannelimage → object (byte / int1 / int2 / uint2 / int4 / real)
Input image.
MaskSize (input_control) integer → (integer)
Required filter size.
Default: 9
List of values: 5, 7, 9, 11, 13
SigmaW (input_control) number → (real / integer)
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
SigmaD (input_control) number → (real / integer)
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
MinGrad (input_control) number → (real / integer)
Threshold for the magnitude of the gradient.
Default: 30.0
Suggested values: 20.0, 15.0, 30.0, 35.0, 40.0
MinApparentness (input_control) number → (real / integer)
Threshold for Apparentness.
Default: 90.0
Suggested values: 30.0, 60.0, 90.0, 150.0, 300.0, 600.0, 1500.0
MinAngle (input_control) angle.rad → (real)
Threshold for the direction change in a corner point (radians).
Default: 0.5
Restriction: (0.0 <= MinAngle) && (MinAngle <= pi)
Subpix (input_control) string → (string)
Subpixel precise calculation of the corner points.
Default: 'false'
List of values: 'false', 'true'
Row (output_control) point.y-array → (real)
Row coordinates of the detected corner points.
Column (output_control) point.x-array → (real)
Column coordinates of the detected corner points.
Result🔗
points_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>). 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