camera_calibration — Determine all camera parameters by a simultaneous minimization process.
camera_calibration performs the calibration of a single camera. For this, known 3D model points (with coordinates NX, NY, NZ) are projected into the image and the sum of the squared distances between the projected 3D-coordinates and their corresponding image point coordinates (NRow, NCol) is minimized.
As initial values for the minimization process the internal (StartCamParam) and external (NStartPose) camera parameters are used. Individual camera parameters can be explicitely included or excluded from the minimization with EstimateParams. For a detailed description of the available camera models, the different sets of internal camera parameters, and general requirements for the setup, see calibrate_cameras.
For a successful calibration, at least one calibration object with accurately known metric properties is needed, e.g., a HALCON calibration plate. Before calling calibrate_cameras, take a series of images of the calibration object in different orientations and make sure that the whole field of view or measurement volume is covered. The success of the calibration highly depends on the quality of the calibration object and the images. So you might want to exercise special diligence during the acquisiton of the calibration images. See the section “How to take a set of suitable images?” in calibrate_cameras for further details.
After a successful calibration, camera_calibration returns the optimized internal (CameraParam) and external (NFinalPose) camera parameters of the camera. Additionally, the root mean square error (RMSE) of the back projection of the optimization is returned in Errors (in pixels). This error gives a general indication whether the optimization was successful.
If a HALCON calibration plate is used, you can use the operator find_calib_object to determine the coordinates of the calibration marks in each image and to compute a rough estimate for the external camera parameters. Using HALCON calibration plates with rectangularly arranged marks (see gen_caltab), a combination of the two operators find_caltab and find_marks_and_pose will have the same effect. In both cases, the hereby obtained values can directly be used as initial values for the external camera parameters (NStartPose).
Obviously, images in which the segmentation of the calibration plate (find_caltab) has failed or the calibration marks have not been determined successfully by find_marks_and_pose or find_calib_object should not be used.
If you use a HALCON calibration plate, the input parameters NX, NY, and NZ are stored in the description file of the calibration plate. You can easily access them by calling the operator caltab_points. Initial values for the internal camera parameters (StartCamParam) can be obtained from the specifications of the used camera. Further information can be found in calibrate_cameras. Initial values for the poses of the calibration plate and the coordinates of the calibration marks NRow and NCol can be calculated using the operator find_calib_object. The tuple NStartPose is set by the concatenation of all these poses.
The input parameter EstimateParams is used to select which camera parameters to estimate. Usually, this parameter is set to 'all', i.e., all 6 external camera parameters (translation and rotation) and all internal camera parameters are determined. If the internal camera parameters already have been determined (e.g., by a previous call to camera_calibration), it is often desired to only determine the pose of the world coordinate system in camera coordinates (i.e., the external camera parameters). In this case, EstimateParams can be set to 'pose'. This has the same effect as EstimateParams = ['alpha','beta','gamma','transx','transy','transz']. Otherwise, EstimateParams contains a tuple of strings that indicates the combination of parameters to estimate. In addition, parameters can be excluded from estimation by using the prefix ~. For example, the values ['pose','~transx'] have the same effect as ['alpha','beta','gamma','transy','transz']. As a different example, ['all','~focus'] determines all internal and external parameters except the focus. The prefix ~ can be used with all parameter values except 'all'.
For additional informations about general limitations when determining camera parameters, please see the section “Limitations” in the reference entry of calibrate_cameras.
The length of the tuple NStartPose depends on the number of calibration images, e.g., using 15 images leads to a length of the tuple NStartPose equal to (15 times the 7 external camera parameters). The first 7 values correspond to the pose of the calibration plate in the first image, the next 7 values to the pose in the second image, etc.
This fixed number of calibration images must be considered within the tuples with the coordinates of the 3D model marks and the extracted 2D marks. If 15 images are used, the length of the tuples NRow and NCol is 15 times the length of the tuples with the coordinates of the 3D model marks (NX, NY, and NZ). If every image consists 49 marks, the length of the tuples NRow and NCol is , while the length of the tuples NX, NY, and NZ is 49. The order of the values in NRow and NCol is “image after image”, i.e., using 49 marks the first 3D model point corresponds to the 1st, 50th, 99th, 148th, 197th, 246th, etc. extracted 2D mark.
If the camera calibration process has finished successfully, the output parameters CameraParam and NFinalPose contain the adjusted values for the internal and external camera parameters. The length of the tuple NFinalPose corresponds to the length of the tuple NStartPose.
The representation types of NFinalPose correspond to the representation type of the first tuple of NStartPose (see create_pose). You can convert the representation type by convert_pose_type.
As an additional parameter, the root mean square error (RMSE) (Errors) of the back projection of the optimization is returned. This parameter reflects the accuracy of the calibration. The error value (root mean square error of the position) is measured in pixels. If only a single camera is calibrated, an Error in the order of 0.1 pixel (the typical detection error by extraction of the coordinates of the projected calibration markers) is an indication that the optimization fits the observation data well. If Errors strongly differs from 0.1 pixels, the calibration did not perform well. Reasons for this might be, e.g., a poor image quality, an insufficient number of calibration images, or an inaccurate calibration plate.
No. The operator camera_calibration is designed in a way that the input tuples NX, NY, NZ, NRow, and NCol can contain any 3D/2D correspondences. The order of the single parameters is explained in the paragraph “What is the order within the individual parameters?”.
Thus, it makes no difference how the required 3D model marks and the corresponding 2D marks are determined. On the one hand, it is possible to use a 3D calibration object, on the other hand, you also can use any characteristic points (e.g. natural landmarks) with known position in the world. By setting EstimateParams to 'pose', it is thus possible to compute the pose of an object in camera coordinates! For this, at least three 3D/2D-correspondences are necessary as input. NStartPose can, e.g., be generated directly as shown in the program example for create_pose.
The minimization process of the calibration depends on the initial values of the internal (StartCamParam) and external (NStartPose) camera parameters. The computed average errors Errors give an impression of the accuracy of the calibration. The errors (deviations in x- and y-coordinates) are measured in pixels.
For line scan cameras, it is possible to set the start value for the internal camera parameter Sy to the value 0.0. In this case, it is not possible to determine the position of the principal point in y-direction. Therefore, EstimateParams must contain the term '~cy'. The effective distance of the principle point from the sensor line is then always . Further information can be found in the section “Limitations” of calibrate_cameras.
Ordered tuple with all x coordinates of the calibration marks (in meters).
Ordered tuple with all y coordinates of the calibration marks (in meters).
Number of elements: NY == NX
Ordered tuple with all z coordinates of the calibration marks (in meters).
Number of elements: NZ == NX
Ordered tuple with all row coordinates of the extracted calibration marks (in pixels).
Ordered tuple with all column coordinates of the extracted calibration marks (in pixels).
Number of elements: NCol == NRow
Initial values for the internal camera parameters.
Number of elements: StartCamParam == 8 || StartCamParam == 10 || StartCamParam == 11 || StartCamParam == 12 || StartCamParam == 14
Ordered tuple with all initial values for the external camera parameters.
Number of elements: NStartPose == 7 * NRow / NX
Camera parameters to be estimated.
Default value: 'all'
List of values: 'all', 'alpha', 'beta', 'camera', 'cx', 'cy', 'focus', 'gamma', 'k1', 'k2', 'k3', 'kappa', 'poly', 'poly_tan_2', 'pose', 'sx', 'sy', 'tilt', 'transx', 'transy', 'transz', 'vx', 'vy', 'vz'
Internal camera parameters.
Number of elements: CameraParam == 8 || CameraParam == 10 || CameraParam == 11 || CameraParam == 12 || CameraParam == 14
Ordered tuple with all external camera parameters.
Number of elements: NFinalPose == 7 * NRow / NX
Average error distance in pixels.
* Read calibration images read_image(Image1, 'calib/calib-01') read_image(Image2, 'calib/calib-02') read_image(Image3, 'calib/calib-03') * Find calibration pattern find_caltab(Image1, CalPlate1, 'caltab_big.descr', 3, 112, 5) find_caltab(Image2, CalPlate2, 'caltab_big.descr', 3, 112, 5) find_caltab(Image3, CalPlate3, 'caltab_big.descr', 3, 112, 5) * Find calibration marks and start poses find_marks_and_pose(Image1, CalPlate1, 'caltab_big.descr', \ [0.008, 0.0, 0.000011, 0.000011, 384, 288, 768, 576], \ 128, 10, 18, 0.9, 15.0, 100.0, RCoord1, CCoord1, \ StartPose1) find_marks_and_pose(Image2, CalPlate2, 'caltab_big.descr', \ [0.008, 0.0, 0.000011, 0.000011, 384, 288, 768, 576], \ 128, 10, 18, 0.9, 15.0, 100.0, RCoord2, CCoord2, \ StartPose2) find_marks_and_pose(Image3, CalPlate3, 'caltab_big.descr', \ [0.008, 0.0, 0.000011, 0.000011, 384, 288, 768, 576], \ 128, 10, 18, 0.9, 15.0, 100.0, RCoord3, CCoord3, \ StartPose3) * Read 3D positions of calibration marks caltab_points('caltab_big.descr', NX, NY, NZ) * Camera calibration camera_calibration(NX, NY, NZ, [RCoord1, RCoord2, RCoord3], \ [CCoord1, CCoord2, CCoord3], \ [0.008, 0.0, 0.000011, 0.000011, 384, 288, 768, 576], \ [StartPose1, StartPose2, StartPose3], 'all', \ CameraParam, NFinalPose, Errors) * Write internal camera parameters to file write_cam_par(CameraParam, 'campar.dat')
camera_calibration returns 2 (H_MSG_TRUE) if all parameter values are correct and the desired camera parameters have been determined by the minimization algorithm. If necessary, an exception is raised.
find_marks_and_pose, caltab_points, read_cam_par
write_pose, pose_to_hom_mat3d, disp_caltab, sim_caltab
find_caltab, find_marks_and_pose, disp_caltab, sim_caltab, write_cam_par, read_cam_par, create_pose, convert_pose_type, write_pose, read_pose, pose_to_hom_mat3d, hom_mat3d_to_pose, caltab_points, gen_caltab, calibrate_cameras