Halcon双相机单标定板标定实现拼图

1.Halcon图像拼接算法在之前的文章里也写过，主要是硬拼接和特征点拼接两种方式，今天增加另一种拼接图像的方式。应用场景是多个相机联合一起拍大尺寸的物体，并且相机视野之间存在重叠区域。通过在同一个标定板上面标定，计算两个相机之间位相对外参矩阵实现拼接。

2.代码分析

dev_update_off ()

*

• Path to the calibration and object images.
  ImagePath := '3d_machine_vision/calibrated_mosaic/'
• Display workflow explanation text.
  dev_close_window ()
  dev_open_window (0, 0, 600, 300, 'black', WindowHandle1)
  set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')
  dev_disp_workflow_text ()
  stop ()
• Display calibration explanation text.
  dev_clear_window ()
  dev_disp_calibration_text ()
  stop ()

dev_close_window ()

dev_open_window (0, 0, 600, 480, 'black', WindowHandle1)

dev_open_window (0, 605, 600, 480, 'black', WindowHandle2)

set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')

set_display_font (WindowHandle2, 16, 'mono', 'true', 'false')

*

---

• *********** Step 1: Calibration of the cameras ***********

---

• Number of calibration images.
  NumCalibImages := 10
• 从每个摄像头读取一张图像，以获得摄像头的宽度和高度。
  read_image (ImageCam1, ImagePath + '/calib_cam_1_01')
  read_image (ImageCam2, ImagePath + '/calib_cam_2_01')
  get_image_size (ImageCam1, WidthCam1, HeightCam1)
  get_image_size (ImageCam2, WidthCam2, HeightCam2)
• 设置内部相机参数的初始值。
  gen_cam_par_area_scan_division (0.012, 0, 4.4e-6, 4.4e-6, WidthCam1 / 2, HeightCam1 / 2, WidthCam1, HeightCam1, StartCamParam1)
  gen_cam_par_area_scan_division (0.012, 0, 4.4e-6, 4.4e-6, WidthCam2 / 2, HeightCam2 / 2, WidthCam2, HeightCam2, StartCamParam2)
• 创建标定模型，并设置参数，此模型同时可以校准两个相机
  create_calib_data ('calibration_object', 2, 1, CalibDataID)
  set_calib_data_cam_param (CalibDataID, 0, [], StartCamParam1)
  set_calib_data_cam_param (CalibDataID, 1, [], StartCamParam2)
  set_calib_data_calib_object (CalibDataID, 0, 'calplate_160mm.cpd')
• 依次访问两个相机的标定板图片，进行标定操作
  for I := 0 to NumCalibImages - 1 by 1
  • Read the calibration images.
    read_image (ImageCam1, ImagePath + '/calib_cam_1_' + (I + 1)KaTeX parse error: Double subscript at position 56: ...+ '/calib_cam_2_̲' + (I + 1)'02d')
  • Find the calibration plate and store observations
  • in the calibration data model.
    find_calib_object (ImageCam1, CalibDataID, 0, 0, I, [], [])
    get_calib_data_observ_contours (ContoursCam1, CalibDataID, 'marks', 0, 0, I)
    find_calib_object (ImageCam2, CalibDataID, 1, 0, I, [], [])
    get_calib_data_observ_contours (ContoursCam2, CalibDataID, 'marks', 1, 0, I)
  • Display calibration images and observed contours.
    dev_set_window (WindowHandle1)
    dev_display (ImageCam1)
    dev_display (ContoursCam1)
    dev_disp_text ('Image ' + (I + 1) + '/' + NumCalibImages + ' (Camera 1)', 'window', 'top', 'left', 'black', [], [])
    dev_set_window (WindowHandle2)
    dev_display (ImageCam2)
    dev_display (ContoursCam2)
    dev_disp_text ('Image ' + (I + 1) + '/' + NumCalibImages + ' (Camera 2)', 'window', 'top', 'left', 'black', [], [])
    disp_continue_message (WindowHandle2, 'black', 'true')
    stop ()
    endfor

*同时校准两个摄像头.

calibrate_cameras (CalibDataID, Errors)

dev_set_window (WindowHandle1)

dev_disp_text ('Calibration successful', 'window', 'top', 'left', 'green', [], [])

dev_set_window (WindowHandle2)

dev_disp_text ('Calibration successful', 'window', 'top', 'left', 'green', [], [])

disp_continue_message (WindowHandle2, 'black', 'true')

stop ()

*

---

• ******************* Step 2: Mosaicking *******************

---

• Display mosaicking explanation text.
  dev_close_window ()
  dev_close_window ()
  dev_open_window (0, 0, 600, 300, 'black', WindowHandle1)
  set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')
  dev_disp_mosaicking_text ()
  stop ()
• Number of objects.
  NumObjects := 2
• Number of images per object.
  NumObjImages := 2
• 获取两个相机各自的标定好的参数，相机内参
  get_calib_data (CalibDataID, 'camera', 0, 'params', CamParam1)
  get_calib_data (CalibDataID, 'camera', 1, 'params', CamParam2)
• 获取相对于第一个相机（参考相机）的位姿
  get_calib_data (CalibDataID, 'calib_obj_pose', [0,0], 'pose', Pose1)
  *设置标定板厚度4mm,注意算子需要用的单位是米m
  set_origin_pose (Pose1, 0, 0, 0.004, Pose1)
• 获取第二台相机相对于第一台相机的位姿.
  get_calib_data (CalibDataID, 'camera', 1, 'pose', RelPose2)
  *为了获得第二个相机的绝对姿态，它的相对姿态需要
  *以被反转并与第一相机的绝对姿态相结合。
  pose_invert (RelPose2, RelPose2Inverted)
  pose_compose (RelPose2Inverted, Pose1, Pose2)

*设置目标图像宽度、高度和比例，以便整个对象

*映射后图像拟合良好。

TargetWidth := 1340

TargetHeight := 800

*像素当量(1颗像素0.0002m),注意单位是m/pixel

Scale := 0.0002

• 设置区域，可以裁剪掉有黑边的图像区域
  Borders := [125,110,665,1222]

*为了映射对象图像，需要校正相机的姿态

*再次取决于物体的厚度。这里我们使用两个不同的对象：

*一把厚度约为2.5mm的尺子和一本薄薄的小册子，可以

*近似为0mm厚度。

HeightCorrections := [-0.0025,0]

*

dev_close_window ()

dev_open_window (0, 0, 600, 480, 'black', WindowHandle1)

dev_open_window (0, 605, 600, 480, 'black', WindowHandle2)

dev_open_window (535, 0, 740, 360, 'black', WindowHandle3)

set_display_font (WindowHandle1, 16, 'mono', 'true', 'false')

set_display_font (WindowHandle2, 16, 'mono', 'true', 'false')

set_display_font (WindowHandle3, 16, 'mono', 'true', 'false')

for OIdx := 0 to NumObjects - 1 by 1

* 设置矫正图像原点位置和标定板厚度

set_origin_pose (Pose1, -0.14, -0.07, HeightCorrections[OIdx], WorldPose1)

set_origin_pose (Pose2, -0.14, -0.07, HeightCorrections[OIdx], WorldPose2)

*

* 生成矫正矩阵

gen_image_to_world_plane_map (Map1, CamParam1, WorldPose1, WidthCam1, HeightCam1, TargetWidth, TargetHeight, Scale, 'bilinear')

gen_image_to_world_plane_map (Map2, CamParam2, WorldPose2, WidthCam1, HeightCam1, TargetWidth, TargetHeight, Scale, 'bilinear')

*

* 矫正图像

for IIdx := 1 to NumObjImages by 1

ObjImageIdx := 2 * OIdx + IIdx

read_image (ImageCam1, ImagePath + '/obj_cam_1_' + ObjImageIdxKaTeX parse error: Double subscript at position 62: ...h + '/obj_cam_2_̲' + ObjImageIdx'02d')

*

* Display input images and camera poses.

dev_set_window (WindowHandle1)

dev_display (ImageCam1)

dev_disp_text ('Camera 1 image', 'window', 'top', 'left', 'black', [], [])

disp_3d_coord_system (WindowHandle1, CamParam1, Pose1, 0.05)

dev_set_window (WindowHandle2)

dev_display (ImageCam2)

dev_disp_text ('Camera 2 image', 'window', 'top', 'left', 'black', [], [])

disp_3d_coord_system (WindowHandle2, CamParam2, Pose2, 0.05)

*

* 通过将图像映射到世界坐标系来优化图像。

map_image (ImageCam1, Map1, ImageWorld1)

map_image (ImageCam2, Map2, ImageWorld2)

*

* 将映射的图像拼接在一起。

get_domain (ImageWorld1, Domain1)

get_domain (ImageWorld2, Domain2)

intersection (Domain1, Domain2, RegionIntersection)

paint_region (RegionIntersection, ImageWorld1, ImageWorld1Blackended, 0, 'fill')

full_domain (ImageWorld1Blackended, ImagePart1)

full_domain (ImageWorld2, ImagePart2)

add_image (ImagePart1, ImagePart2, ImageFull, 1, 0)

*

* Rotate image and remove the black borders for display.

rotate_image (ImageFull, ImageRotated, 12, 'constant')

gen_rectangle1 (RectangleDomain, Borders[0], Borders[1], Borders[2], Borders[3])

reduce_domain (ImageRotated, RectangleDomain, ImageReduced)

crop_domain (ImageReduced, ImageReduced)

mirror_image (ImageReduced, ImageReduced, 'row')

mirror_image (ImageReduced, ImageResult, 'column')

*

* Display the result image.

dev_set_window (WindowHandle3)

dev_display (ImageResult)

dev_disp_text ('Result image', 'window', 'top', 'left', 'black', [], [])

if (ObjImageIdx < NumObjects * NumObjImages)

disp_continue_message (WindowHandle3, 'black', 'true')

stop ()

else

dev_disp_text ('End of program', 'window', 'bottom', 'right', 'black', [], [])

endif

endfor

endfor