hough_circles — Detect centers of circles for a specific radius using the Hough transform.
hough_circles detects the centers of circles in regions
with the help of the Hough transform
for circles with a specific radius.
RegionIn (input_object) region → object
Binary edge image in which the circles are to be detected.
RegionOut (output_object) region(-array) → object
Centers of those circles which are included in the edge image by Percent percent.
Number of elements: RegionOut == Radius * Percent * Mode
Radius (input_control) integer(-array) → (integer)
Radius of the circle to be searched in the image.
Number of elements: 1 <= Radius <= 500
Default value: 12
Typical range of values: 2
≤
Radius
≤
500 (lin)
Minimum increment: 1
Recommended increment: 1
Percent (input_control) integer(-array) → (integer)
Indicates the percentage (approximately) of the (ideal) circle which
must be present in the edge image RegionIn.
Number of elements: 1 <= Percent <= 100
Default value: 60
Typical range of values: 10
≤
Percent
≤
100 (lin)
Minimum increment: 1
Recommended increment: 5
Mode (input_control) integer(-array) → (integer)
The mode defines the position of the circle in question:
0 - the radius is equivalent to the outer border of the set pixels.
1 - the radius is equivalent to the centers of the circle lines' pixels.
2 - both 0 and 1 (a little more fuzzy, but more reliable in contrast to
circles set slightly differently, necessitates 50 %
more processing capacity compared to 0 or 1 alone).
Number of elements: 1 <= Mode <= 3
List of values: 0, 1, 2
The operator hough_circles returns the value TRUE
if the input is not empty.
The behavior in case of empty input (no input regions available) is
set via the operator set_system('no_object_result',<Result>),
the behavior in case of empty region is set via
set_system('empty_region_result',<Result>).
If necessary an exception is raised.
Foundation