Name
find_caltabfind_caltabFindCaltabfind_caltabFindCaltabFindCaltab — Segment the region of a standard calibration plate with rectangularly
arranged marks in the image.
Herror find_caltab(const Hobject Image, Hobject* CalPlate, const char* CalPlateDescr, const Hlong SizeGauss, const Hlong MarkThresh, const Hlong MinDiamMarks)
Herror T_find_caltab(const Hobject Image, Hobject* CalPlate, const Htuple CalPlateDescr, const Htuple SizeGauss, const Htuple MarkThresh, const Htuple MinDiamMarks)
Herror find_caltab(Hobject Image, Hobject* CalPlate, const HTuple& CalPlateDescr, const HTuple& SizeGauss, const HTuple& MarkThresh, const HTuple& MinDiamMarks)
HRegion HImage::FindCaltab(const HTuple& CalPlateDescr, const HTuple& SizeGauss, const HTuple& MarkThresh, const HTuple& MinDiamMarks) const
HRegion HImageArray::FindCaltab(const HTuple& CalPlateDescr, const HTuple& SizeGauss, const HTuple& MarkThresh, const HTuple& MinDiamMarks) const
void FindCaltab(const HObject& Image, HObject* CalPlate, const HTuple& CalPlateDescr, const HTuple& SizeGauss, const HTuple& MarkThresh, const HTuple& MinDiamMarks)
HRegion HImage::FindCaltab(const HString& CalPlateDescr, const HTuple& SizeGauss, const HTuple& MarkThresh, Hlong MinDiamMarks) const
HRegion HImage::FindCaltab(const HString& CalPlateDescr, Hlong SizeGauss, Hlong MarkThresh, Hlong MinDiamMarks) const
HRegion HImage::FindCaltab(const char* CalPlateDescr, Hlong SizeGauss, Hlong MarkThresh, Hlong MinDiamMarks) const
static void HOperatorSet.FindCaltab(HObject image, out HObject calPlate, HTuple calPlateDescr, HTuple sizeGauss, HTuple markThresh, HTuple minDiamMarks)
HRegion HImage.FindCaltab(string calPlateDescr, HTuple sizeGauss, HTuple markThresh, int minDiamMarks)
HRegion HImage.FindCaltab(string calPlateDescr, int sizeGauss, int markThresh, int minDiamMarks)
find_caltabfind_caltabFindCaltabfind_caltabFindCaltabFindCaltab is used to determine the region of a plane
calibration plate with circular marks in the input image
ImageImageImageImageImageimage. The region must correspond to a standard calibration plate
with rectangularly arranged marks described in the file
CalPlateDescrCalPlateDescrCalPlateDescrCalPlateDescrCalPlateDescrcalPlateDescr. The successfully segmented
region is returned in CalPlateCalPlateCalPlateCalPlateCalPlatecalPlate. The operator provides two algorithms.
By setting appropriate integer values in SizeGaussSizeGaussSizeGaussSizeGaussSizeGausssizeGauss,
MarkThreshMarkThreshMarkThreshMarkThreshMarkThreshmarkThresh, and MinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksminDiamMarks, respectively, you invoke
the standard algorithm. If you pass a tuple of parameter names in
SizeGaussSizeGaussSizeGaussSizeGaussSizeGausssizeGauss and a corresponding tuple of parameter values in
MarkThreshMarkThreshMarkThreshMarkThreshMarkThreshmarkThresh, or just two empty tuples, respectively, you invoke the
advanced algorithm instead. In this case the value passed in
MinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksminDiamMarks is ignored.
Standard algorithm
First, the input image is smoothed (see gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage); the size of
the used filter mask is given by SizeGaussSizeGaussSizeGaussSizeGaussSizeGausssizeGauss. Afterwards, a
threshold operator (see thresholdthresholdThresholdthresholdThresholdThreshold) with a minimum gray value
MarkThreshMarkThreshMarkThreshMarkThreshMarkThreshmarkThresh is applied. Among the extracted connected regions
the most convex region with an almost correct number of holes (corresponding
to the dark marks of the calibration plate) is selected. Holes with a
diameter smaller than the expected size of the marks
MinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksMinDiamMarksminDiamMarks are eliminated to reduce the impact of noise.
The number of marks is read from the calibration plate description
file CalPlateDescrCalPlateDescrCalPlateDescrCalPlateDescrCalPlateDescrcalPlateDescr. The complete explanation of this file
can be found within the description of gen_caltabgen_caltabGenCaltabgen_caltabGenCaltabGenCaltab.
Advanced algorithm
First, an image pyramid based on ImageImageImageImageImageimage is built. Starting from the
highest pyramid level, round regions are segmented with a dynamic threshold.
Then, they are associated in groups based on their mutual proximity and
it is evaluated whether they can represent marks of a potential
calibration plate. The search is terminated once the expected number of
marks has been identified in one group. The surrounding lighter area
is returned in CalPlateCalPlateCalPlateCalPlateCalPlatecalPlate.
The image pyramid makes the search independent from the size of the image
and the marks. The dynamic threshold makes the algorithm immune to bad or
irregular illumination. Therefore, in general, no parameter is required.
Yet, you can adjust some auxiliary parameters of the advanced algorithm
by passing a list of parameter names (strings) to SizeGaussSizeGaussSizeGaussSizeGaussSizeGausssizeGauss and
a list of corresponding parameter values to MarkThreshMarkThreshMarkThreshMarkThreshMarkThreshmarkThresh. Currently
the following parameter is supported:
- 'gap_tolerance'"gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance":
-
Tolerance factor for gaps between the marks. If the marks appear
closer to each other than expected, you might set
'gap_tolerance'"gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance" < 1.0 to avoid disturbing patterns
outside the calibration plate to be associated with the calibration
plate. This can typically happen if the plate is strongly tilted and
positioned in front of a background that exposes mark-like patterns.
If the distances between single marks deviate significantly, e.g., if
the calibration plate appears with strong perspective distortion in the
image, you might set 'gap_tolerance'"gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance" > 1.0 to enforce
the grouping for the more distant marks.
Suggested values: 0.75, 0.9,
1.0 (default),
1.1, 1.2, 1.5
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Automatically parallelized on tuple level.
File name of the calibration plate description.
Default value:
'caltab.descr'
"caltab.descr"
"caltab.descr"
"caltab.descr"
"caltab.descr"
"caltab.descr"
List of values: 'caltab.descr'"caltab.descr""caltab.descr""caltab.descr""caltab.descr""caltab.descr", 'caltab_100mm.descr'"caltab_100mm.descr""caltab_100mm.descr""caltab_100mm.descr""caltab_100mm.descr""caltab_100mm.descr", 'caltab_10mm.descr'"caltab_10mm.descr""caltab_10mm.descr""caltab_10mm.descr""caltab_10mm.descr""caltab_10mm.descr", 'caltab_200mm.descr'"caltab_200mm.descr""caltab_200mm.descr""caltab_200mm.descr""caltab_200mm.descr""caltab_200mm.descr", 'caltab_30mm.descr'"caltab_30mm.descr""caltab_30mm.descr""caltab_30mm.descr""caltab_30mm.descr""caltab_30mm.descr"
File extension: .descr
Filter size of the Gaussian.
Default value: 3
List of values: 0, 3, 5, 7, 9, 11, 'gap_tolerance'"gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance""gap_tolerance"
Threshold value for mark extraction.
Default value: 112
List of values: 48, 64, 80, 96, 112, 128, 144, 160, 0.5, 0.9, 1.0, 1.1, 1.5
Expected minimal diameter of the marks on the calibration
plate.
Default value: 5
List of values: 3, 5, 9, 15, 30, 50, 70
* read calibration image
read_image(Image, 'calib-01')
* find calibration pattern
find_caltab(Image, CalPlate, 'caltab.descr', 3, 112, 5)
* read calibration image
read_image(Image, 'calib-01')
* find calibration pattern
find_caltab(Image, CalPlate, 'caltab.descr', 3, 112, 5)
* read calibration image
read_image(Image, 'calib-01')
* find calibration pattern
find_caltab(Image, CalPlate, 'caltab.descr', 3, 112, 5)
// read calibration image
HImage Image("calib-01") ;
// find calibration pattern
HRegion CalPlate = Image.FindCaltab("caltab.descr", 3,112, 5);
* read calibration image
read_image(Image, 'calib-01')
* find calibration pattern
find_caltab(Image, CalPlate, 'caltab.descr', 3, 112, 5)
* read calibration image
read_image(Image, 'calib-01')
* find calibration pattern
find_caltab(Image, CalPlate, 'caltab.descr', 3, 112, 5)
find_caltabfind_caltabFindCaltabfind_caltabFindCaltabFindCaltab returns 2 (H_MSG_TRUE) if all parameter values are
correct and an image region is found. The behavior in case
of empty input (no image given) can be set via
set_system(::'no_object_result',<Result>:)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)
and the behavior in case of an empty result region via
set_system(::'store_empty_region',<'true'/'false'>:)set_system("store_empty_region",<"true"/"false">)SetSystem("store_empty_region",<"true"/"false">)set_system("store_empty_region",<"true"/"false">)SetSystem("store_empty_region",<"true"/"false">)SetSystem("store_empty_region",<"true"/"false">).
If necessary, an exception is raised.
read_imageread_imageReadImageread_imageReadImageReadImage
find_marks_and_posefind_marks_and_poseFindMarksAndPosefind_marks_and_poseFindMarksAndPoseFindMarksAndPose
find_marks_and_posefind_marks_and_poseFindMarksAndPosefind_marks_and_poseFindMarksAndPoseFindMarksAndPose,
camera_calibrationcamera_calibrationCameraCalibrationcamera_calibrationCameraCalibrationCameraCalibration,
disp_caltabdisp_caltabDispCaltabdisp_caltabDispCaltabDispCaltab,
sim_caltabsim_caltabSimCaltabsim_caltabSimCaltabSimCaltab,
caltab_pointscaltab_pointsCaltabPointscaltab_pointsCaltabPointsCaltabPoints,
gen_caltabgen_caltabGenCaltabgen_caltabGenCaltabGenCaltab
Foundation