Operators |
find_caltab — Segment the region of a standard calibration plate with rectangularly arranged marks in the image.
find_caltab(Image : CalPlate : CalPlateDescr, SizeGauss, MarkThresh, MinDiamMarks : )
find_caltab is used to determine the region of a plane calibration plate with circular marks in the input image Image. The region must correspond to a standard calibration plate with rectangularly arranged marks described in the file CalPlateDescr. The successfully segmented region is returned in CalPlate. The operator provides two algorithms. By setting appropriate integer values in SizeGauss, MarkThresh, and MinDiamMarks, respectively, you invoke the standard algorithm. If you pass a tuple of parameter names in SizeGauss and a corresponding tuple of parameter values in MarkThresh, or just two empty tuples, respectively, you invoke the advanced algorithm instead. In this case the value passed in MinDiamMarks is ignored.
First, the input image is smoothed (see gauss_image); the size of the used filter mask is given by SizeGauss. Afterwards, a threshold operator (see threshold) with a minimum gray value MarkThresh 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 MinDiamMarks are eliminated to reduce the impact of noise. The number of marks is read from the calibration plate description file CalPlateDescr. The complete explanation of this file can be found within the description of gen_caltab.
First, an image pyramid based on Image 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 CalPlate.
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 SizeGauss and a list of corresponding parameter values to MarkThresh. Currently the following parameter is supported:
Tolerance factor for gaps between the marks. If the marks appear closer to each other than expected, you might set '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' > 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
Input image.
Output region.
File name of the calibration plate description.
Default value: 'caltab.descr'
List of values: 'caltab.descr' , 'caltab_100mm.descr' , 'caltab_10mm.descr' , 'caltab_200mm.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'
Threshold value for mark extraction.
Default value: 112
Suggested 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
Suggested values: 3, 5, 9, 15, 30, 50, 70
* Read calibration image. read_image(Image, 'calib/calib_distorted_01') * Find calibration pattern. find_caltab(Image, CalPlate, 'caltab_100mm.descr', 3, 112, 5)
find_caltab 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>:) and the behavior in case of an empty result region via set_system(::'store_empty_region',<'true'/'false'>:). If necessary, an exception is raised.
find_marks_and_pose, camera_calibration, disp_caltab, sim_caltab, caltab_points, gen_caltab
Foundation
Operators |