halcon中的常用算子的中文说明

1、sub_image (ImageConverted1, ImageConverted2, ImageSub, 1, 0)一幅图减另一幅图。用一幅图的灰度减另一幅的灰度成新的一幅图。mult_image (Image, ImagePart, ImageResult, 0.015, 0)一幅图加一幅成的一幅图convert_image_type (Traffic2, ImageConverted2, 'int2')转换图像的格式crop_part (ImageNoise, ImagePart, 0, 0, Width, Height)取出一幅图的中部分dots_image (Ima

2、geResult, DotImage, 5, 'dark', 2)取出图像中圆点partition_dynamic (SelectedRegions, Partitioned, 25, 20)根据各个区域的特征将各个区域分割开。intersection (Partitioned, Region, Characters)取出两个区域中重叠的部分，如果Region有两个区域在Partitioned中，则这两个区域合并成一区域。difference (RegionDilation, RegionErosion, RegionDifference) 取出两个区域中不重叠的部分。crit

3、ical_points_sub_pix (FilterResponse, 'facet', 1.5, 0.7, RowMin, ColMin, RowMax, ColMax, RowSaddle, ColSaddle)取出图像中的关键点。corner_response (Image, FilterResponse, 3, 0.04)auto_threshold (Image, Regions, 10)自动阈值分割，根据灰度直方图中两波峰中的波谷取出阈值。closing (RegionClosing3, Rectangle, RegionClosing4)用一个设计好的区域来封闭

4、其它区域。hom_mat2d_identity (HomMat2DIdentity)生成一个2D单位矩阵hom_mat3d_identity (HomMat3DIdentity)生成一个3D单位矩阵hom_mat2d_translate (HomMat2DIdentity, -0.5*(Row1+Row2), -0.5*(Column1+Column2), HomMat2DTranslate)对矩阵进行2D变换，用于平移。hom_mat3d_rotate (HomMat3DIdentity, GraspPhiZ_ref, 'z', 0, 0, 0, HomMat3D_RZ_Ph

5、i) 对矩阵进行3D变换，用于旋转。hom_mat3d_translate (HomMat3D_RZ_Phi, CenterPointX_ref, CenterPointY_ref, 0, ref_H_grasp) 对矩阵进行3D变换，用于平移。hom_mat2d_scale (HomMat2DTranslate, ScaleFactor, ScaleFactor, 0, 0, HomMat2DScale) 对矩阵进行变换，用于缩放hom_mat3d_compose (cam_H_ref, ref_H_grasp, cam_H_grasp)将两矩阵相乘hom_mat3d_to_pose (ca

6、m_H_grasp, PoseCamGripper)将矩阵变换成3D位姿affine_trans_contour_xld (LogoContoursTemp, LogoContours, HomMat2DComplete)对线条LogoContoursTemp进行HomMat2DComplete对应的变换（平移和缩放）。compose3 (ImageRed, ImageGreen, ImageBlue, LogoImageTempl)将三幅图像合并成一幅图像decompose3 (LogoImage, ImageR, ImageG, ImageB)将一幅图像根据RGB值转换成三幅图像。pain

7、t_xld (LogoContours, LogoImageTempl, LogoImage, Blue,Orange,Blue,Blue,Blue,Blue)对线条喷颜色。Blue := 0,48,117，Orange := 255,181,41check_difference (Traffic1, Traffic2, Selected1, 'diff_outside', -255, 15, 0, 0, 0)根据两幅图的不同进行图像分割。bin_threshold自动阈值分割，与auto_threshold (Image, Regions, 10)类似，但只有一个最小值取得仅

8、有一个阈值。char_threshold (Alpha1, Alpha1, Characters, 6, 95, Threshold)自动阈值分割，阈值根据直方图的波峰取得dyn_threshold (ImageFilled, ImageMean, RegionDynThresh, 3, 'light')动态阈值分割。gray_histo (Alpha1, Alpha1, AbsoluteHisto, RelativeHisto)获得绝对与相对直方。background_seg (Edges, BackgroundRegions)将找出的区域根据背景分割成各个连通的区域。fil

9、l_up_shape (BackgroundRegions, RegionFillUp, 'area', 1, 40)有选择性的填充smooth_funct_1d_gauss (Function, Sigma, SmoothedFunction)对一维数组进行平滑处理。funct_1d_to_pairs (SmoothedFunction, XValues, YValues)将数据分别对应赋予一个横坐标。fill_interlace (Image, ImageFilled, 'odd')修改在采集图像过程中造成的两个半幅图像拼接的问题。regiongrowing

10、 (Image, Regions, 1, 1, 1, 100)将图像分割成各个灰度值相近的区域。expand_gray_ref (Regions, Image, EmptyRegion, RegionExpand, 'maximal', 'image', Mean, 11)根据灰度和颜色将分离的区域连通。expand_line (Image, RegionExpand, Line, 'mean', 'row', 100)将轮廓拓展成一个跟其灰度相近的区域。expand_region (Regions, NoPixel, Regio

11、nExpanded1, 'maximal', 'image') 根据设定的特征将分离的区域连通。fast_threshold (Image, Region, 128, 255, 10)根据最大和最小灰度以及面积选出区域gray_erosion_rect (Image, Imag, StrokeWidth, StrokeWidth)每个点的灰度值用这个点的矩形掩码内最小灰度值代替。select_shape_std (ConnectedRegions, SelectedRegion, 'max_area', 70)从多个区域选出指定特征相似的区域。如

12、选出面积最大的区域。scale_image_max (ImageReduced, ImageScaleMax)增加图像的对比度text_line_orientation (SelectedRegion, ImageScaleMax, 30, rad(-30), rad(30), OrientationAngle) 检测具有字符的图像的方向rotate_image (ImageScaleMax, ImageRotate, deg(-OrientationAngle), 'constant')将图像按照指定的角度旋转find_text (ImageRotate, TextModel

13、, TextResult)根据设定的模板寻找字符get_mposition (WindowHandleButton, Row, Column, Button)获得鼠标坐标gen_grid_region (RegionGrid, Gap, Gap, 'lines', Width, Height)生成网格区域clip_region (Grid, StreetGrid, 165, 20, 405, 750)选择一定范围内的区域。clip_region_rel (RegionBorder, RegionClipped, 5, 5, 5, 5)选择四边都减去一定像素的区域gray_clo

14、sing (Image, ImageReduced, ImageClosingFast)灰度值闭操作gray_opening (Image, ImageReduced, ImageOpeningFast) 灰度值开操作hysteresis_threshold (EdgeAmplitude, RegionHysteresis, 10, 20, 10)当大于最大阈值的点取出做为可靠点，最大与最小值之间的点根据与可靠点的关系选出。get_domain (Image, Domain)得到整幅图像的区域gen_rectangle1 (Rectangle, Row1, Column1, Row2, Col

15、umn2)在区域内部的实心区域得到一个平行于横坐标的最大矩形。complement(Region : RegionComplement : : )找到输入区域的补区域。interjacent (Regions, RegionInterjacent, 'border')找到将各个区域分割开的区域local_max (Image, LocalMaxima)找到比周围灰度值都大的点。local_min (ImageInverted, LocalMinima) 找到比周围灰度值都小的点smooth_image (Image, ImageSmooth, 'deriche2'

16、;, 0.2)平滑图像invert_image (ImageSmooth, ImageInverted)用255减去每个点的灰度值作为这个点新的灰度值。shape_trans (RegionFillUp, Pads, 'convex')根据指定的参数对区域的形状进行转换，如转换成正方形等。select_shape_proto (Pads, BallBonds, MissingBonds, 'overlaps_rel', 0, 0)选出具有相似特征的所有区域boundary (RegionIntersection, RegionBorder, 'inner

17、')获得区域的边界lines_gauss (ImageReducedTracks, Lines, 1.5, 1, 8, 'light', 'true', 'true', 'true')提取图的线条并计算出图的宽度。get_contour_xld (Line, Row, Column)获得线条的各个点的坐标min_max_gray (ImageAngioMedian, ImageAngioMedian, 0, Min, Max, Range)获得区域内图像的最大和最小灰度值median_rect (ImageNeedle,

18、ImageNeedleMedian, 41, 41)对图像中值滤波shape_trans_xld (Border, XLDConvex, 'convex')将区域的边界根据不同的属性转化成线条get_contour_attrib_xld (Line, 'width_left', WidthL)得到线上每个点的属性fit_circle_contour_xld (ObjectSelected, 'ahuber', -1, 2, 0, 3, 2, Row, Column, Radius, StartPhi, EndPhi, PointOrder)将线条

19、拟合成圆，得到位置和半径。gen_circle_contour_xld (ContCircle, Row, Column, Radius, 0, rad(360), 'positive', 1.0)生成一个圆get_contour_global_attrib_xld (ObjectSelected, 'cont_approx', Attrib)返回线条的全局属性值，当Attrib<0时线条是直线，当Attrib>0时是圆弧。clip_contours_xld (Lines, LinesClipped, Top, Left, Bottom, Right

20、)选择一定区域内的线条clip_end_points_contours_xld (EllipseContour, ClippedContoursLength, 'length', 20)去除线条两端的部分像素。region_to_bin (Rectangle, BinImage, 130, 100, 120, 130)将区域转换成具有固定灰度值的图像paint_gray (SmoothedImage, BinImage, Image)将一图图像绘制到另一幅图像上。union_collinear_contours_xld (RegressContours, UnionContou

21、rs, 10, 1, 2, 0.1, 'attr_keep')连接共线的线条。gen_contour_polygon_xld (Contour4, 200,200,300,300,200, 320,450,450,300,300)生成任意多边曲线close_contours_xld (Contours, ClosedContours)让不封闭的线条封闭select_contours_xld (Contours, SelectedContours, 'closed', 0, 20, 0, 0)选择一定条件的线条。crop_contours_xld (Lines,

22、LinesCropped, Top - 0.5, Left - 0.5, Bottom + 0.5, Right + 0.5, 'false')提取出一定范围内的线条。gen_polygons_xld (Contour1, Polygon1, 'ramer', 10)将线条拟合成多边形。dev_set_part (239, 197, 239+17, 197+17)设置显示的区域dev_set_color ('cyan')设置显示的颜色dev_set_draw ('margin')设置显示的区域是填充还是空心的dev_set_sha

23、pe ('ellipse') 设置显示的区域的形状select_region_point (Regions, DestRegions, Row, Column)选择包含指定点的区域gen_contour_region_xld (SelectedRegions, Contours, 'border_holes')根据区域和指定的特征生成轮廓线。dump_window_image (DumpImage, WindowHandle)将窗口的内容截图成图像area_center_points_xld (ClipContours, Area, RowPoints, Col

24、umnPoints)轮廓线所有点计算的中心area_center_xld (ClipContours, Area, Row, Column, PointOrder)轮廓线所有的区域的中心gen_nurbs_interp (Rows, Cols, 0,-10,0,10, 3, CtrlRows, CtrlCols, Knots)根据提供的点拟合成曲线的坐标gen_contour_nurbs_xld (Contour, CtrlRows, CtrlCols, Knots, 'auto', 3, 1, 5)根据拟合的坐标生成轮廓线gen_parallel_contour_xld (E

25、dges, ParallelEdgesAngle, 'contour_normal', 3)根据指定的特征生成相应的平行线。get_grayval_contour_xld (Image, Contour, 'bilinear', Grayval)提取了轮廓线上所有点的灰度值test_subset_region(Region1, Region2 : : : IsSubset)测试一个区域是不是在另一个区域中。subset(Rows,Min)从数组Rows先出Min对应序列的数组create_funct_1d_array (Grayval, Function)根据数

26、组生成一个函数序列local_min_max_funct_1d (Function, 'strict_min_max', 'false', Min, Max)提取出函数序列中的局部最大和最小值。dev_inspect_ctrl (PoseRobotGrasp_ZYX)打开检测窗口dev_close_inspect_ctrl (PoseRobotGrasp_ZYX)关闭检测窗口pose_to_hom_mat3d (PoseCamBase, cam_H_base)将3D位姿转换成一个矩阵。disp_3d_coord_system (WindowHandle, Cam

27、Param, PoseCamRef, 0.01)根据内参和外参显示3D坐标系concat_obj (Lines, Contour, Lines)将对象合并，可以分类时将属性相同的人为合并成一类。gen_parallels_xld (Polygon, ParallelLines, 50, 100, rad(10), 'true')找到平行的轮廓线get_parallels_xld (ParallelLines, Row1, Col1, Length1, Phi1, Row2, Col2, Length2, Phi2)得到平行轮廓线的相关坐标。affine_trans_point_

28、3d (cam_H_ref, GraspPointsX_ref, GraspPointsY_ref, 0, 0, GraspPointsX_cam, GraspPointsY_cam, GraspPointsZ_cam)对点进行3D变换。project_3d_point (GraspPointsX_cam, GraspPointsY_cam, GraspPointsZ_cam, CamParam, GraspPointsRow, GraspPointsCol)将空间的3D坐标变换到图像坐标union_cocircular_contours_xld (ContoursSplit, UnionCo

29、ntours, 0.9, 0.5, 0.5, 200, 50, 50, 'true', 1)将属于同一个圆的轮廓线连接起来sort_index(Length)|Length|-1+1找出最大值对应的索引polar_trans_image (ImageReduced, ImagePolar, Row, Column, PolarResolution, Radius+5)把图像由笛卡尔坐标转换成极坐标下图像，及把圆环形的图像区域转换成矩形区域。polar_trans_region_inv (RegionUnion, XYTransRegion, Row, Column, 6.283

30、19, 0, Radius-RingSize, Radius, 640, RingSize, 1280, 1024, 'nearest_neighbor') 把图像由极坐标坐标转换成笛卡尔下图像，及把矩形的图像区域转换成圆环形区域。rotate_image (ImagePart, ImageRotate, 90, 'constant')将图像旋转90度lines_color (Image, Lines, 3.5, 0, 12, 'true', 'false')检测图像中颜色线条，并提取出它们的宽度。Measure_circle提取

31、圆弧线的例子：intersection_ll( : : RowA1, ColumnA1, RowA2, ColumnA2, RowB1, ColumnB1, RowB2, ColumnB2 : Row, Column, IsParallel)提取两条交叉直线交叉点的坐标orientation_region (Region, OrientationRegion)提取区域的方向obj_diff (ConnectedRegions, LeftRegions, RightRegions)提取两组对象中不同的对象。optical_flow_mg (Image1, Image2, VectorField,

32、 'clg', 1, 1, 1000, 5, 'default_parameters', 'fast')计算两幅图像中的视觉差异，用于监控。vector_field_length (VectorField, LengthImage, 'squared_length')计算向量的长度，得到差异图像。local_max_sub_pix (ImageReduced, 'facet', 1.0, 4, Row, Column)提取出图像中灰度极大值的坐标mod_parallels_xld (ParallelRoadEdge

33、s, Part, ModParallelRoadEdges, ExtParallelRoadEdges, 0.3, 160, 220, 10)修补平行的轮廓线split_contours_xld (Polygons, SplitContours, 'polygon', 1, 5)regress_contours_xld (SplitContours, RegressContours, 'drop', 1)select_xld_point (Contours, SelectedContours, PointRow, PointCol)选择包含指定点的轮廓线。sym

34、m_difference_closed_contours_xld (BoundarySet1, BoundarySet2, ContoursDifference)提取封闭对称轮廓线的不同部分test_self_intersection_xld (Contours, 'false', DoesIntersect)检测轮廓线本身是否存在交叉点test_xld_point (Contour1, PointRow, PointCol, IsInsideContour1)测试提供的点是否被轮廓线包含在内union2_closed_contours_xld (BoundarySet1, B

35、oundarySet2, ContoursUnion)从多条轮廓线中合并成封闭的轮廓线union2_closed_polygons_xld (BoundarySet1, BoundarySet2, PolygonsUnion)从多个多边形的轮廓线中提取封闭的轮廓线。union_cotangential_contours_xld (ContourConcat4, UnionContours4, FitClippingLength, FitLength, TestMaxTangAngle, MaxDist, MaxDistPerp, MaxOverlap, 'attr_forget'

36、;)tile_images (Images4, TiledImage3, 2, 'horizontal')将幅图像合并成一幅图像select_contours_xld (RegressContours, SelectedContours, 'curvature', 0, 0.5, 0, 0)根据线的特征选择轮廓线。select_shape_xld (SelectedContours, SelectedEdges, 'contlength', 'and', 15, 500)根据线的形态特征选择轮廓线。vector_to_proj_h

37、om_mat2d (RowUL,RowUR,RowLR,RowLL+0.5, ColUL,ColUR,ColLR,ColLL+0.5, 160,160,340,340+0.5, 250,550,550,250+0.5, 'normalized_dlt', , , , , , , HomMat2D, Covariance)根据图像坐标和实际坐标得到坐标的变换关系。union_collinear_contours_ext_xld (UnionContours, UnionContours, MaxDistAbs, MaxDistRel, 5, 0.5, 0, -1, 1, 1, 1

38、, 1, 1, 0, 'attr_keep')连接同线的轮廓线，提取的轮廓比union_collinear_contours_xld更精准。orientation_points_xld (WireSegment, RefOrientation)corner_response (ImaAmp, ImageCorner, 3, 0.04)提取图像中的角gen_parallels_xld (Polygon, ParallelLines, 50, 100, rad(10), 'true')找到平行的直线十.双目视觉系统标定 (2012-04-25 00:45:

39、33)转载标签： it halcon 计算机视觉 机器视觉1.get_image_pointer1(Image : : : Pointer, Type, Width, Height)返回第一通道的点，图像数据类型，图像尺寸。2.disp_image(Image : : WindowHandle : )在输出窗口显示灰度图像3.visualize_results_of_find_marks_and_pose (ImageL, WindowHandle1, RCoordL, CC

40、oordL, StartPoseL, StartCamParL)内部函数，显示初步标定的坐标系和MARKS中心，MARKS中线用十字线标出。4.set_calib_data_observ_points( : : CalibDataID, CameraIdx, CalibObjIdx,CalibObjPoseIdx, Row, Column, Index, Pose : )储存以点为基础的标定观测值，将观测值储存与标定数据句柄中。5.calibrate_cameras( : : CalibDataID

41、60;: Error)根据标定数据模型中的值标定摄像机。6.get_calib_data( : : CalibDataID, ItemType, ItemIdx, DataName : DataValue)查询储存或计算得到的标定模型中的数据。7.write_cam_par( : : CameraParam, CamParFile : )把相机内参数写入TXT文件8.write_pose( : : Pose, PoseFile : )把相机的位姿写入TXT文件9.g

42、en_binocular_rectification_map( : Map1, Map2 : CamParam1, CamParam2, RelPose,SubSampling, Method, MapType : CamParamRect1, CamParamRect2, CamPoseRect1,CamPoseRect2, RelPoseRect)把相机参数和姿态作为输入，输出为校正图像和矫正后的参数和姿态。10.map_image(Image, Ma

43、p : ImageMapped : : )dev_update_window ('off')* Set the image pathImgPath := '3d_machine_vision/stereo/'* Read the first images to get their sizei := 0read_image (ImageL, ImgPath+'calib_distorted_l_'+i$'03d')read_image (ImageR, ImgPath+'calib_distor

44、ted_r_'+i$'03d') /分别读取左右目图像，编号长3位/* Reopen the windows with an appropriate sizedev_close_window ()dev_close_window ()get_image_pointer1 (ImageL, PointerL, TypeL, WidthL, HeightL)get_image_pointer1 (ImageR, PointerR, TypeR, WidthR, HeightR)dev_open_window (0, 0, WidthL, HeightL, '

45、;black', WindowHandle1)dev_open_window (0, WidthL+5, WidthL, HeightL, 'black', WindowHandle2)/为左右目各打开一                               

46、                                         个图形窗口/* Set the calibration plate description fileCalt

47、abName := 'caltab_30mm.descr'* Set the initial values for the interior camera parametersStartCamParL := 0.0125, 0, 7.4e-6, 7.4e-6,WidthL/2.0,HeightL/2.0,WidthL,HeightLStartCamParR := StartCamParL* parameter settings for find_caltab and find_marks_and_poseSizeGauss := 3MarkThresh := 120MinDia

48、mMarks := 5StartThresh := 128DeltaThresh := 10MinThresh := 18Alpha := 0.9MinContLength := 15MaxDiamMarks := 100* Create a calibration data model in which all calibration data* including the image coordinates of the calibration marks and* the observation poses of the calibration plate will be* accumu

49、latedcreate_calib_data ('calibration_object', 2, 1, CalibDataID)      /创建标定数据模型句柄/set_calib_data_cam_param (CalibDataID, 0, 'area_scan_division', StartCamParL)/在标定模型中              

50、0;                                                 

51、0;    设置相机的类型和原始参数/set_calib_data_cam_param (CalibDataID, 1, 'area_scan_division', StartCamParR)set_calib_data_calib_object (CalibDataID, 0, CaltabName)        /定义一个标定对象/* Start the loop over the calibration imagesfor i := 0 to 10 b

52、y 1    * Read and display the calibration images    read_image (ImageL, ImgPath+'calib_distorted_l_'+i$'03d')    read_image (ImageR, ImgPath+'calib_distorted_r_'+i$'03d')    disp_image (Im

53、ageL, WindowHandle1)    disp_image (ImageR, WindowHandle2)                         /读取并显示图像/    * Search for the calibration plate 

54、; find_caltab (ImageL, CaltabL, CaltabName, SizeGauss, MarkThresh, MinDiamMarks)  find_caltab (ImageR, CaltabR, CaltabName, SizeGauss, MarkThresh, MinDiamMarks)/输出标定板区域/    disp_region (CaltabL, WindowHandle1)    disp_region (CaltabR, WindowHand

55、le2)                     /显示标定区域/              * Extract the calibration marks and estimate an initial pose   

56、 find_marks_and_pose (ImageL, CaltabL, CaltabName, StartCamParL, StartThresh, DeltaThresh, MinThresh, Alpha, MinContLength, MaxDiamMarks, RCoordL, CCoordL, StartPoseL)    * Visualize the extracted calibration marks and the    * coordinate system defined b

57、y the estimated pose.    visualize_results_of_find_marks_and_pose (ImageL, WindowHandle1, RCoordL, CCoordL, StartPoseL, StartCamParL)                      /显示初步标定的坐标系和MAR

58、KS中心/    * Extraction of marks and pose as well as visualization of the    * results for the second image.    find_marks_and_pose (ImageR, CaltabR, CaltabName, StartCamParR, StartThresh, DeltaThresh, MinThresh, Alpha, MinContLength, MaxDiam

59、Marks, RCoordR, CCoordR, StartPoseR)    visualize_results_of_find_marks_and_pose (ImageR, WindowHandle2, RCoordR, CCoordR, StartPoseR, StartCamParR)    * Store the image coordinates of the calibration marks as well    * as the estimated ini

60、tial poses for all stereo pairs in the    * calibration data model    *  - Camera 0 is the (L)eft camera    *  - Camera 1 is the (R)ight camera    set_calib_data_observ_points (CalibDataID, 0, 0, i, R

61、CoordL, CCoordL, 'all', StartPoseL)    set_calib_data_observ_points (CalibDataID, 1, 0, i, RCoordR, CCoordR, 'all', StartPoseR)                       

62、;                                 /在标定数据模型句柄中储存标定结果/endfor* Perform the actual calibrationcalibrate_cameras (CalibDataID, Errors) 

63、        /根据标定数据模型中的值标定摄像机/* Get the calibrated camera parametersget_calib_data (CalibDataID, 'camera', 0, 'params', CamParamL)get_calib_data (CalibDataID, 'camera', 1, 'params', CamParamR)      /获取摄

64、像机参数/* Since the left camera is the reference camera for the* calib data model, the pose of the right camera is its* pose relative to the left cameraget_calib_data (CalibDataID, 'camera', 1, 'pose', cLPcR)    /获取右目相对于左目的位姿/* Store the results into fileswrite_cam_p

65、ar (CamParamL, 'cam_left-125.dat')write_cam_par (CamParamR, 'cam_right-125.dat')write_pose (cLPcR, 'pos_right2left.dat')                    /将相机参数写入文件/* Generate the rectificat

66、ion mapsgen_binocular_rectification_map (MapL, MapR, CamParamL, CamParamR, cLPcR, 1, 'geometric', 'bilinear', RectCamParL, RectCamParR, CamPoseRectL, CamPoseRectR, RectLPosRectR) /把相机参数和姿态作为输入，输出为校正图像和矫正后的参数和姿态。/* Read in a stereo image pair, aquired with the stereo camera syste

67、m,* which has been calibrated, just now.read_image (ImageL, ImgPath+'caliper_distorted_l')read_image (ImageR, ImgPath+'caliper_distorted_r')* Rectify the stereo images and display themmap_image (ImageL, MapL, ImageRectifiedL)map_image (ImageR, MapR, ImageRectifiedR)dev_set_window (Wi

68、ndowHandle1)dev_clear_window ()dev_display (ImageRectifiedL)dev_set_window (WindowHandle2)dev_clear_window ()dev_display (ImageRectifiedR)disp_continue_message (WindowHandle1, 'black', 'true')stop ()dev_set_window (WindowHandle2)dev_close_window ()dev_update_window ('on')dev_

69、set_window (WindowHandle1)dev_clear_window ()dev_display (ImageRectifiedL)clear_calib_data (CalibDataID)十二.图像获取与相关参数（halcon) (2012-04-25 21:02:38)转载标签： it halcon 计算机视觉 机器视觉图像获取程序例1.1.set_system( : : SystemParameter, Value : )设置系统参数2.open_framegrabber ( : : Name, HorizontalResolution,Vertical