HALCON从入门到入门-找边找圆工具的使用

测试效果

步骤解析

1.创建计算模型

create_metrology_model (MetrologyHandle)

2.设置模型的图像宽高

set_metrology_model_image_size (MetrologyHandle, Width, Height)

3.添加测量工具，这里是添加了圆形检测工具

add_metrology_object_rectangle2_measure (MetrologyHandle, RectangleInitRow, RectangleInitColumn, RectangleInitPhi, RectangleInitLength1, RectangleInitLength2, RectangleTolerance, 5, .5, 1, [], [], MetrologyRectangleIndices)

4.添加矩形 检测工具

add_metrology_object_rectangle2_measure (MetrologyHandle, RectangleInitRow, RectangleInitColumn, RectangleInitPhi, RectangleInitLength1, RectangleInitLength2, RectangleTolerance, 5, .5, 1, [], [], MetrologyRectangleIndices)

5.设置检测模型参数

set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'num_instances', 2)

6.设置检测模型方向 （由明到暗还是相反）

set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'measure_transition', 'uniform')

7.设置最小得分

set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'min_score', .9)

8.将这个测量模型应用到图像上

apply_metrology_model (Image, MetrologyHandle)

9.获取测量结果

get_metrology_object_result (MetrologyHandle, MetrologyRectangleIndices, 'all', 'result_type', 'all_param', RectangleParameter)

10.把找到的点获取到 显示出来

get_metrology_object_measures (Contour, MetrologyHandle, 'all', 'all', Row1, Column1)

gen_cross_contour_xld (Cross, Row1, Column1, 6, 0.785398)

测试代码

* This example shows the usage of the metrology model
* to measure circles and rectangles with subpixel
* accuracy under challenging conditions easily.
* 
* Display initializations
dev_update_off ()
read_image (Image, 'pads')
get_image_size (Image, Width, Height)
dev_close_window ()
dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)
set_display_font (WindowHandle, 14, 'mono', 'true', 'false')
* 
* Define the approximate position and the measure
* tolerance for the circles
RowCircle := [52:89:500]
CircleInitRow := [RowCircle,RowCircle]
CircleInitColumn := [gen_tuple_const(6,348),gen_tuple_const(6,438)]
gen_cross_contour_xld (Cross1, CircleInitRow, CircleInitColumn, 6, 0.785398)
CircleInitRadius := [gen_tuple_const(6,23),gen_tuple_const(6,23)]
CircleRadiusTolerance := 12
* Define the approximate position and the measure
* tolerance for the rectangles
RectangleInitRow := [410,410]
RectangleInitColumn := [215,562]
RectangleInitPhi := [0,0]
RectangleInitLength1 := [85,85]
RectangleInitLength2 := [88,88]
RectangleTolerance := 10
* 
* Prepare the metrology model data structure
create_metrology_model (MetrologyHandle)
* Setting the image width in advance is not
* necessary, but improves the runtime of the
* first measurement.
set_metrology_model_image_size (MetrologyHandle, Width, Height)
* Add the metrology rectangle objects to the model
* as defined above
add_metrology_object_rectangle2_measure (MetrologyHandle, RectangleInitRow, RectangleInitColumn, RectangleInitPhi, RectangleInitLength1, RectangleInitLength2, RectangleTolerance, 5, .5, 1, [], [], MetrologyRectangleIndices)
* Add the metrology circle objects to the model
* as defined above
add_metrology_object_circle_measure (MetrologyHandle, CircleInitRow, CircleInitColumn, CircleInitRadius, CircleRadiusTolerance, 5, 1.5, 2, [], [], MetrologyCircleIndices)
* It is possible to measure more than one circle/rectangle/line/ellipse
* instance per metrology object in one call.
* Since we like to measure two circles per object,
* we set 'num_instances' to 2.
set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'num_instances', 2)
* Setting 'measure_transition' to 'uniform' assures
* that only consistent circles are returned, that have
* either only edges from bright to dark or vice versa.
* Since the consistency check increases runtime, it is
* switched of by default.
* In this example however, it is safer to switch it on,
* because both negative and positive edges are present.
set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'measure_transition', 'uniform')
* Setting the minimum score can make the results more robust
set_metrology_object_param (MetrologyHandle, MetrologyCircleIndices, 'min_score', .9)
* 
* Perform the measurement
* 
apply_metrology_model (Image, MetrologyHandle)
* 
get_metrology_object_result (MetrologyHandle, MetrologyRectangleIndices, 'all', 'result_type', 'all_param', RectangleParameter)
* Extract the parameters for better readability
Sequence := [0:5:|RectangleParameter| - 1]
RectangleRow := RectangleParameter[Sequence]
RectangleColumn := RectangleParameter[Sequence + 1]
RectanglePhi := RectangleParameter[Sequence + 2]
RectangleLength1 := RectangleParameter[Sequence + 3]
RectangleLength2 := RectangleParameter[Sequence + 4]
* 
* Access the results of the circle measurement
get_metrology_object_result (MetrologyHandle, MetrologyCircleIndices, 'all', 'result_type', 'all_param', CircleParameter)
* Extract the parameters for better readability
Sequence := [0:3:|CircleParameter| - 1]
CircleRow := CircleParameter[Sequence]
CircleColumn := CircleParameter[Sequence + 1]
CircleRadius := CircleParameter[Sequence + 2]
* 
* Display the results
* 
* Get measured contours
get_metrology_object_result_contour (Contours, MetrologyHandle, 'all', 'all', 1.5)
* Get the contours of the measure regions
* and the coordinates of the edge points
* that were the basis for fitting the circles and rectangles
get_metrology_object_measures (Contour, MetrologyHandle, 'all', 'all', Row1, Column1)
gen_cross_contour_xld (Cross, Row1, Column1, 6, 0.785398)
* Display everything
Color := ['gray','cyan','green']
dev_display (Image)
dev_set_line_width (1)
dev_set_color (Color[0])
dev_display (Contour)
dev_set_color (Color[1])
dev_display (Cross)
dev_set_line_width (2)
dev_set_color (Color[2])
dev_display (Contours)
Message := Color[2] + ': Measurement result'
Message[1] := Color[1] + ': Edge candidate points'
Message[2] := Color[0] + ': Measure regions'
disp_message (WindowHandle, Message, 'window', 12, 12, 'black', 'true')