前言

1卡尺工具介紹

Halcon中的Metrology方法即為卡尺工具，可用來擬合線，圓，這種方法對于目標比背景很明顯的圖像尺寸測量是很方便的，不需要用blob進行邊緣提取等，但缺點也很明顯，需要目標的相對位置基本不變才行。
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2匹配方法概念

HDevelop開發環境中提供的匹配的方法有三種，即Component-Based、Gray-Value-Based、Shape-Based,分別是基于組件的匹配，基于灰度值的匹配和基于形狀的匹配，本文所用的例程方法為基于形狀的匹配。

例程詳解

**模型的名字為基于形狀的匹配方法
AlignmentMode := 'shape-based matching'
* AlignmentMode := 'region processing'（區域）
* AlignmentMode := 'rigid transformation'（剛性變換）
* 
* 初始化視圖
dev_update_off ()
dev_close_window ()
dev_set_draw ('margin')
gen_empty_obj (EmptyObject)
read_image (Image, 'metal-parts/circle_plate_01')
get_image_size (Image, Width, Height)
dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)
set_display_font (WindowHandle, 16, 'mono', 'true', 'false')

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* Part I:
* 
* 初始化卡尺模型
* 定義相機參數
gen_cam_par_area_scan_division (0.0128649, -661.434, 5.30004e-006, 5.3e-006, 620.043, 497.402, Width, Height, CameraParam)
* 測量平面的位姿是通過標定板標定得到的，懂標定的自然懂。
MeasurementPlane := [0.00940956,-0.00481017,0.29128,0.478648,359.65,0.785,0]
* 根據零件的高度和校準板的高度調整測量平面的位姿
CalibPlateThickness := 0.006
PartHeight := 0.005
AdjustThickness := CalibPlateThickness - PartHeight
set_origin_pose (MeasurementPlane, 0, 0, AdjustThickness, MeasurementPlaneAdjusted)
* 
* 創建標定模型并準備標定測量
create_metrology_model (MetrologyHandle)
* 提前設置圖像大小，以加快第一次調用apply_metrology_model的速度
set_metrology_model_image_size (MetrologyHandle, Width, Height)
* 在卡尺模型里設置相機參數
set_metrology_model_param (MetrologyHandle, 'camera_param', CameraParam)
* 設置被測對象的位姿
set_metrology_model_param (MetrologyHandle, 'plane_pose', MeasurementPlaneAdjusted)
* 
* Add the objects to be measured to the metrology model
* 
* 添加圓的參數（由上圖可知有四個完整的圓）：行列坐標，半徑
CircleParam := [354,274,53]
CircleParam := [CircleParam,350,519,53]
CircleParam := [CircleParam,345,764,52]
CircleParam := [CircleParam,596,523,53]
add_metrology_object_generic (MetrologyHandle, 'circle', CircleParam, 20, 5, 1, 30, [], [], CircleIndices1)
* 
* 添加兩個殘缺的圓。
CircleParam1 := [583,1010,79]
CircleParam2 := [336,1005,77]
*角度不同，故寫了兩次
add_metrology_object_generic (MetrologyHandle, 'circle', CircleParam1, 20, 5, 1, 30, ['start_phi','end_phi'], [0,rad(185)], CircleIndices2)
add_metrology_object_generic (MetrologyHandle, 'circle', CircleParam2, 20, 5, 1, 30, ['start_phi','end_phi'], [rad(45),rad(185)], Index3)
CircleIndices2 := [CircleIndices2,Index3]
* 
* 添加一個矩形
RectangleParam := [599,279,rad(90),62,51]
add_metrology_object_generic (MetrologyHandle, 'rectangle2', RectangleParam, 20, 5, 1, 30, [], [], RectIndices)* 添加兩條線（邊界線）
Line1 := [143,1122,709,1132]
Line2 := [151,153,136,1115]
add_metrology_object_generic (MetrologyHandle, 'line', [Line1,Line2], 20, 5, 1, 30, [], [], LineIndices)
* 檢查已添加到計量模型中的形狀
get_metrology_object_model_contour (ModelContour, MetrologyHandle, 'all', 1.5)
get_metrology_object_measures (MeasureContour, MetrologyHandle, 'all', 'all', Row, Column)
Message := 'This example shows how to measure geometric shapes using a'
Message[1] := 'metrology model. As preparation, their roughly known '
Message[2] := 'dimensions and tolerances are specified by the user.'
show_contours (Image, ModelContour, MeasureContour, EmptyObject, WindowHandle, Message)
stop ()

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* Part 2:
* 
* 準備匹配
* 
* a) Shape-based matching
if (AlignmentMode == 'shape-based matching')dev_set_part (-Height / 2 - 100, -Width / 2, 1.5 * Height - 100, 1.5 * Width)* * 創建用于圖像中計量模型匹配的形狀模型，其中對象的位置和方向與用于創建模型的圖像中對象的位置和方向不同。* 得到當前halcon系統的參數值get_system ('border_shape_models', BorderShapeModel)set_system ('border_shape_models', 'true')*閾值處理并截取區域threshold (Image, Region, 0, 50)dilation_rectangle1 (Region, ModelRegion, 5, 5)reduce_domain (Image, ModelRegion, ImageReduced)*創建用于匹配的模型：參數（Template : : 金字塔級的數量, 起始角度, 角度范圍, 角度的步長，優化的類型, 匹配度規, 閾值, 目標最小對比值 : ModelID）create_shape_model (ImageReduced, 6, 0, rad(360), 'auto', 'auto', 'use_polarity', 'auto', 20, ShapeModelID)*將模型的原點設置為輸入區域的中心area_center (ModelRegion, Area, RowModel, ColumnModel)*得到形狀模型的輪廓get_shape_model_contours (ShapeModelContours, ShapeModelID, 1)Message := 'A shape model will be used for the alignment of the metrology'Message[1] := 'model. The contours of the shape model (white) and of the'Message[2] := 'metrology model (blue) are shown.'show_contours (Image, ModelContour, EmptyObject, ShapeModelContours, WindowHandle, Message)* * 更改定義卡尺模型的參考系統，使之與形狀模型所使用的對應。set_metrology_model_param (MetrologyHandle, 'reference_system', [RowModel,ColumnModel,0])*得到卡尺模型的輪廓，參數：（模型輪廓，句柄，卡尺測量對象的索引，相鄰兩個輪廓點的距離get_metrology_object_model_contour (ModelContour, MetrologyHandle, 'all', 1.5)Message := 'To prepare the alignment, the origin of the shape model'Message[1] := 'is set as the reference system of the metrology model.'show_contours (Image, ModelContour, EmptyObject, ShapeModelContours, WindowHandle, Message)stop ()dev_set_part (0, 0, Height - 1, Width - 1)
endif
*

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*另外兩種匹配模型：基于區域和仿射變換。

* b) Region processing
if (AlignmentMode == 'region processing')* Determine reference position and orientationthreshold (Image, Region, 0, 50)fill_up (Region, RegionFillUp)difference (RegionFillUp, Region, OriginalRegion)area_center (OriginalRegion, Area, RowOrig, ColumnOrig)orientation_region (OriginalRegion, AngleOrig)* Change the reference system of the metrology modelset_metrology_model_param (MetrologyHandle, 'reference_system', [RowOrig,ColumnOrig,AngleOrig])
endif
* 
* c) Rigid transformation
if (AlignmentMode == 'rigid transformation')* Reference points:extract_reference_points (Image, RowReference, ColumnReference)gen_cross_contour_xld (ReferencePoints, RowReference, ColumnReference, 15, 0.785398)dev_display (Image)dev_set_color ('white')dev_display (ReferencePoints)Message := 'To prepare the alignment, reference points are extracted.'disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')disp_message (WindowHandle, [1:4], 'image', RowReference, ColumnReference, 'black', 'true')stop ()
endif
*

* 線上階段
for I := 2 to 5 by 1read_image (CurrentImage, 'metal-parts/circle_plate_' + I$'02d')dev_set_line_width (1)dev_display (CurrentImage)* * a) Shape-based matchingif (AlignmentMode == 'shape-based matching')* * 測量物體的位置和方向，使用find_shape_model算子。* 參數：（測試圖，句柄，搜索角度，范圍，模型實例的最小分數，模型數量，最大重疊度，亞像素精度，金字塔層數，* 搜索貪婪度（這個值在很大程度上影響著搜索速度，若為0，則為啟發式搜索，若為1，則為不安全搜索），模型的行坐標，列坐標，角度，分數）find_shape_model (CurrentImage, ShapeModelID, 0, rad(360), 0.5, 1, 0, 'least_squares', 5, 0.9, RowAlign, ColumnAlign, AngleAlign, Score)dev_display_shape_matching_results (ShapeModelID, 'white', RowAlign, ColumnAlign, AngleAlign, 1, 1, 0)endif* * b) Region processingif (AlignmentMode == 'region processing')* Determine the current position and orientationthreshold (CurrentImage, Region, 0, 50)fill_up (Region, RegionFillUp)difference (RegionFillUp, Region, CurrentRegion)area_center (CurrentRegion, Area, RowAlign, ColumnAlign)orientation_region (CurrentRegion, AngleAlign)endif* * c) Rigid transformationif (AlignmentMode == 'rigid transformation')* Referenzpunkte:extract_reference_points (CurrentImage, RowExtracted, ColumnExtracted)gen_cross_contour_xld (ExtractedPoints, RowExtracted, ColumnExtracted, 15, 0.785398)dev_display (CurrentImage)dev_set_color ('white')dev_display (ExtractedPoints)disp_message (WindowHandle, [1:4], 'image', RowExtracted, ColumnExtracted, 'black', 'true')vector_to_rigid (RowReference, ColumnReference, RowExtracted, ColumnExtracted, HomMat2D)hom_mat2d_to_affine_par (HomMat2D, Sx, Sy, AngleAlign, Theta, RowAlign, ColumnAlign)endif

    * * 使用計算的位置和方向將計量模型與當前發生的事件對齊align_metrology_model (MetrologyHandle, RowAlign, ColumnAlign, AngleAlign)* 展示匹配效果if (I <= 2)**展示提取的輪廓get_metrology_object_model_contour (ModelContour, MetrologyHandle, 'all', 1.5)dev_set_color ('blue')dev_set_line_width (2)dev_display (ModelContour)Message := 'In each image, the object is matched and aligned'Message[1] := 'before the metrology measurement.'disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')disp_continue_message (WindowHandle, 'black', 'true')stop ()endif* *在一次調用中對所有計量對象執行測量apply_metrology_model (CurrentImage, MetrologyHandle)* 獲取測量區域以進行可視化get_metrology_object_measures (Contour, MetrologyHandle, 'all', 'all', Row, Column)* 獲取用于擬合幾何形狀的邊緣點get_metrology_object_result (MetrologyHandle, 'all', 'all', 'used_edges', 'row', UsedRow)get_metrology_object_result (MetrologyHandle, 'all', 'all', 'used_edges', 'column', UsedColumn)gen_cross_contour_xld (UsedEdges, UsedRow, UsedColumn, 10, rad(45))* * 獲取測量結果* 由于設置了攝像機參數，所有結果都以相對于測量平面所定義的坐標系的度量坐標給出* * 得到所有的輪廓目標get_metrology_object_result_contour (ResultContours, MetrologyHandle, 'all', 'all', 1.5)* 提取小圓的半徑get_metrology_object_result (MetrologyHandle, CircleIndices1, 'all', 'result_type', 'radius', RadiusC1)* 提取較大的不完整圓的半徑get_metrology_object_result (MetrologyHandle, CircleIndices2, 'all', 'result_type', 'radius', RadiusC2)* 提取矩形邊的長度get_metrology_object_result (MetrologyHandle, RectIndices, 'all', 'result_type', 'length1', Length1R)get_metrology_object_result (MetrologyHandle, RectIndices, 'all', 'result_type', 'length2', Length2R)* 獲取每條測量線的起點和終點get_metrology_object_result (MetrologyHandle, LineIndices[0], 'all', 'result_type', 'all_param', ParamLine1)get_metrology_object_result (MetrologyHandle, LineIndices[1], 'all', 'result_type', 'all_param', ParamLine2)* Display the resultsdev_display (CurrentImage)dev_set_line_width (1)dev_set_color ('light gray')dev_display (Contour)dev_set_color ('green')dev_set_line_width (2)dev_display (ResultContours)dev_set_line_width (1)dev_set_color ('white')dev_display (UsedEdges)* * 顯示圓心處每個圓的半徑* 獲取圓心的度量坐標get_metrology_object_result (MetrologyHandle, CircleIndices1, 'all', 'result_type', 'x', XC1)get_metrology_object_result (MetrologyHandle, CircleIndices1, 'all', 'result_type', 'y', YC1)* 將圓心的度量坐標投影到圖像中，得到圓心的圖像坐標project_xy_to_image (XC1, YC1, MeasurementPlaneAdjusted, CameraParam, Row1, Column1)get_metrology_object_result (MetrologyHandle, CircleIndices2, 'all', 'result_type', 'x', XC2)get_metrology_object_result (MetrologyHandle, CircleIndices2, 'all', 'result_type', 'y', YC2)project_xy_to_image (XC2, YC2, MeasurementPlaneAdjusted, CameraParam, Row2, Column2)disp_message (WindowHandle, 'r=' + (RadiusC1 * 1000)$'.2f', 'image', Row1, Column1 - 80, 'black', 'true')disp_message (WindowHandle, 'r=' + (RadiusC2 * 1000)$'.2f', 'image', Row2, Column2 - 80, 'black', 'true')get_metrology_object_result (MetrologyHandle, RectIndices, 'all', 'result_type', 'x', XRectangle)get_metrology_object_result (MetrologyHandle, RectIndices, 'all', 'result_type', 'y', YRectangle)project_xy_to_image (XRectangle, YRectangle, MeasurementPlaneAdjusted, CameraParam, RowR, ColumnR)Area := Length1R * Length2R * 4 * 1000 * 1000disp_message (WindowHandle, 'area=' + Area$'.2f', 'image', RowR, ColumnR - 120, 'black', 'true')Message := 'Measured metric results after alignment (r in mm, area in mm^2):'* disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')if (I < 5)disp_continue_message (WindowHandle, 'black', 'true')endifstop ()endfor
if (AlignmentMode == 'shape-based matching')set_system ('border_shape_models', BorderShapeModel)
endif

總結

卡尺工具在halcon中的使用比較簡單，基于匹配的卡尺測量分為以下幾個步驟:

創建卡尺模型，添加測量項信息，create_metrology_model ，add_metrology_object_generic。
創建用于形狀匹配的匹配模型，create_shape_model。
用匹配模型與實際圖像進行匹配，find_shape_model
展示匹配結果，get_metrology_object_model_contour，apply_metrology_model，get_metrology_object_measures，get_metrology_object_result。