halcon 测量拟合 一维测量

一、一维测量的原理

原理：灰度投影+导数（最小幅度值）[Halcon&测量] 一维测量_Loewen丶的小窝-CSDN博客_halcon一维测量

1、Halocn的一维测量首先构建矩形或者扇形的ROI测量对象，然后在ROI内画出等距离的、长度与ROI宽度一致的、垂直于ROI的轮廓线（profile line）的等距线

2、测量ROI的轮廓线尽量与被测边缘垂直，宽度适当宽些

3、然后，沿着垂直轮廓线的方向，计算出每一条等距线的平均灰度值，可以得出轮廓线的灰度直方图，同时可以选择使用高斯滤波器平滑灰度直方图

4、求出平滑灰度直方图的一阶导数，（一阶导数为最大，二阶导数为0）一阶导数的极值点作为边缘的亚像素精度候选点，只有一阶导数极值点的绝对值大于预先设定的阈值（测量算子的参数Threshold）边缘候选点才被选作为边缘中心点（沿着刨分线的放向的一阶导数）

二、原理解释

【Halcon】1D测量-工业视觉/halcon-少有人走的路

1、什么是轮廓线？什么是切片？

 2、计算平均灰度值

 

 3、如何提取边缘

 三、流程

1、采集图像（灰度图）

2、测量矩形或者是测量弧形

 测量矩形

gen_measure_rectangle2 (Row, Column, Angle, Length1, Length2, Width, Height, 'bilinear', MeasureHandle)

*生成一个测量的卡尺
*gen_measure_rectangle2：确定测量的矩形的具体位置
*Row (input_control)：矩形中心点的行坐标
*Column (input_control)：矩形中心点的列坐标
*Phi (input_control)：刨分线与水平方向的夹角（弧度制）
*Length1 (input_control)：矩形长轴的一半
*Length2 (input_control)：矩形短轴的一半
*Width (input_control) ：待处理图像的宽度
*Height (input_control) ：待处理图像的高度
*Interpolation (input_control) ：插值方式（‘bicubic’, ‘bilinear’,‘nearest_neighbor’）
*MeasureHandle (output_control) ：测量对象句柄

测量弧形

gen_measure_arc( : : CenterRow, CenterCol, Radius, AngleStart, AngleExtent, AnnulusRadius, Width, Height, Interpolation : MeasureHandle)
名字：生成环形区域测量句柄
描述：用于提取垂直环形圆弧的直边缘。
参数：
CenterRow：圆弧中心行坐标
CenterCol：圆弧中心列坐标
Radius：圆弧半径
AngleStart：圆弧起始角度
AngleExtent：圆弧角度范围
AnnulusRadius：环形带的半径（宽度的一半）
Width：图像的宽度
Height：图像的高度
Interpolation ：插值类型
MeasureHandle：测量对象句柄

3、测量 边缘对

measure_pairs - 提取垂直于矩形或环形弧的直边对



measure_pairs (Fuse, MeasureHandle, 1, 1, 'negative', 'all', RowEdgeFirst, ColumnEdgeFirst, AmplitudeFirst, RowEdgeSecond, ColumnEdgeSecond, AmplitudeSecond, IntraDistance, InterDistance)

* 提取垂直于矩形或者是弧形的直边对
* 单通道的图像
* 上面定义的测量句柄
* 高斯模糊的Sigma的值，Sigma指定了高斯滤波器的标准差  ，Sigma越大图像越平缓，高斯函数（正太分布）
* 最小边缘幅度值，越大则检测到的边就越少，和canny算子的那个滞后阈值处理一样理解
* 边缘如何成对，'negative'   postive  :沿着 刨分线的方向由暗到亮维为正     all:
* 选择找点的模式（all： 所有的点，first 输出所有的点， last 输出最后一个点）
* 边缘对第一条边的中心行的坐标（2个值）
* 边缘对第一条边列的坐标
* 两条边的边缘幅度值，有符号的
* 边缘对第二条边的中心行的坐标（2个值）
* 边缘对第二条边列的坐标
* 两条边的边缘幅度值，有符号的


***  边缘对内部之间的距离
***  连续边缘对之间的距离

 

 

 

边缘 

measure_pos(Image : : MeasureHandle, Sigma, Threshold, Transition, Select : RowEdge, ColumnEdge, Amplitude, Distance)
Image (input_object) ：输入图像
MeasureHandle (input_control) ：测量对象句柄
Sigma (input_control) ：Sigma指定了高斯滤波器的标准差。 高斯滤波参数，越大越平滑
Threshold (input_control) ：边缘强度控制阈值，最小边缘幅度
Transition (input_control) ：边界从白到黑还是从黑到白（分别对          应’negative’,‘positive’，也可以选择‘all’）这个是得到矩形的那个方向
Select (input_control) ：选择寻点的模式（ 'all’输出所有点, 'first’输出第一个点, 'last’输出最后一个点）
下面四个是
RowEdge (output_control) ：寻到直边的中心点行坐
ColumnEdge (output_control) ：寻到直边的中心点列坐标
Aplitude (output_control) ：寻到直边的边缘强度值
Distance (output_control) ：连续边之间的距离

 

极性

上面极性写错了， 弃明投暗是negative ,反之就是positive

位置：

dev_update_window ('off')
dev_close_window ()
* ****
* （1）获取图像
* ****
read_image (Fuse, 'fuse')
get_image_size (Fuse, Width, Height)

* Measure 02: Code generated by Measure 02
* Measure 02: Prepare measurement
AmplitudeThreshold := 31
RoiWidthLen2 := 32.5
set_system ('int_zooming', 'false')
* Measure 02: Coordinates for line Measure 02 [0]
LineRowStart_Measure_02_0 := 379.889
LineColumnStart_Measure_02_0 := 554.367
LineRowEnd_Measure_02_0 := 214.226
LineColumnEnd_Measure_02_0 := 559.762
* Measure 02: Convert coordinates to rectangle2 type
TmpCtrl_Row := 0.5*(LineRowStart_Measure_02_0+LineRowEnd_Measure_02_0)
TmpCtrl_Column := 0.5*(LineColumnStart_Measure_02_0+LineColumnEnd_Measure_02_0)
TmpCtrl_Dr := LineRowStart_Measure_02_0-LineRowEnd_Measure_02_0
TmpCtrl_Dc := LineColumnEnd_Measure_02_0-LineColumnStart_Measure_02_0
TmpCtrl_Phi := atan2(TmpCtrl_Dr, TmpCtrl_Dc)
TmpCtrl_Len1 := 0.5*sqrt(TmpCtrl_Dr*TmpCtrl_Dr + TmpCtrl_Dc*TmpCtrl_Dc)
TmpCtrl_Len2 := RoiWidthLen2
* Measure 02: Create measure for line Measure 02 [0]
* Measure 02: Attention: This assumes all images have the same size!
gen_measure_rectangle2 (TmpCtrl_Row, TmpCtrl_Column, TmpCtrl_Phi, TmpCtrl_Len1, TmpCtrl_Len2, 768, 576, 'nearest_neighbor', MsrHandle_Measure_02_0)
* Measure 02: ***************************************************************
* Measure 02: * The code which follows is to be executed once / measurement *
* Measure 02: ***************************************************************
* Measure 02: The image is assumed to be made available in the
* Measure 02: variable last displayed in the graphics window
copy_obj (Fuse, Image, 1, 1)
* Measure 02: Execute measurements
measure_pairs (Image, MsrHandle_Measure_02_0, 6.1, AmplitudeThreshold, 'all', 'all', Row1_Measure_02_0, Column1_Measure_02_0, Amplitude1_Measure_02_0, Row2_Measure_02_0, Column2_Measure_02_0, Amplitude2_Measure_02_0, Width_Measure_02_0, Distance_Measure_02_0)
* Measure 02: Do something with the results
gen_cross_contour_xld (Cross1, Row1_Measure_02_0, Column1_Measure_02_0, 169, 0.785398)
gen_cross_contour_xld (Cross2, Row2_Measure_02_0, Column2_Measure_02_0, 169, 0.785398)



















* Measure 01: Code generated by Measure 01
* Measure 01: Prepare measurement
AmplitudeThreshold := 47
RoiWidthLen2 := 41.5
set_system ('int_zooming', 'true')
* Measure 01: Coordinates for line Measure 01 [0]
LineRowStart_Measure_01_0 := 290.671
LineColumnStart_Measure_01_0 := 473.746
LineRowEnd_Measure_01_0 := 292.784
LineColumnEnd_Measure_01_0 := 717.229
* Measure 01: Convert coordinates to rectangle2 type
TmpCtrl_Row := 0.5*(LineRowStart_Measure_01_0+LineRowEnd_Measure_01_0)
TmpCtrl_Column := 0.5*(LineColumnStart_Measure_01_0+LineColumnEnd_Measure_01_0)
TmpCtrl_Dr := LineRowStart_Measure_01_0-LineRowEnd_Measure_01_0
TmpCtrl_Dc := LineColumnEnd_Measure_01_0-LineColumnStart_Measure_01_0
TmpCtrl_Phi := atan2(TmpCtrl_Dr, TmpCtrl_Dc)
TmpCtrl_Len1 := 0.5*sqrt(TmpCtrl_Dr*TmpCtrl_Dr + TmpCtrl_Dc*TmpCtrl_Dc)
TmpCtrl_Len2 := RoiWidthLen2
* Measure 01: Create measure for line Measure 01 [0]
* Measure 01: Attention: This assumes all images have the same size!
gen_measure_rectangle2 (TmpCtrl_Row, TmpCtrl_Column, TmpCtrl_Phi, TmpCtrl_Len1, TmpCtrl_Len2, 768, 576, 'nearest_neighbor', MsrHandle_Measure_01_0)
* Measure 01: ***************************************************************
* Measure 01: * The code which follows is to be executed once / measurement *
* Measure 01: ***************************************************************
* Measure 01: The image is assumed to be made available in the
* Measure 01: variable last displayed in the graphics window
copy_obj (Fuse, Image, 1, 1)
* Measure 01: Execute measurements
measure_pos (Image, MsrHandle_Measure_01_0, 3.1, AmplitudeThreshold, 'all', 'all', Row_Measure_01_0, Column_Measure_01_0, Amplitude_Measure_01_0, Distance_Measure_01_0)
* Measure 01: Do something with the results

gen_cross_contour_xld (Cross, Row_Measure_01_0, Column_Measure_01_0, 100, 0.785398)

read_image (Image, 'ic_pin')
get_image_size (Image, Width, Height)
* Measure 03: Code generated by Measure 03
* Measure 03: Prepare measurement
AmplitudeThreshold := 38
RoiWidthLen2 := 6.5
set_system ('int_zooming', 'true')
* Measure 03: Coordinates for line Measure 03 [0]
LineRowStart_Measure_03_0 := 56.1067
LineColumnStart_Measure_03_0 := 60.1518
LineRowEnd_Measure_03_0 := 62.4751
LineColumnEnd_Measure_03_0 := 930.307
* Measure 03: Convert coordinates to rectangle2 type
TmpCtrl_Row := 0.5*(LineRowStart_Measure_03_0+LineRowEnd_Measure_03_0)
TmpCtrl_Column := 0.5*(LineColumnStart_Measure_03_0+LineColumnEnd_Measure_03_0)
TmpCtrl_Dr := LineRowStart_Measure_03_0-LineRowEnd_Measure_03_0
TmpCtrl_Dc := LineColumnEnd_Measure_03_0-LineColumnStart_Measure_03_0
TmpCtrl_Phi := atan2(TmpCtrl_Dr, TmpCtrl_Dc)
TmpCtrl_Len1 := 0.5*sqrt(TmpCtrl_Dr*TmpCtrl_Dr + TmpCtrl_Dc*TmpCtrl_Dc)
TmpCtrl_Len2 := RoiWidthLen2
* Measure 03: Create measure for line Measure 03 [0]
* Measure 03: Attention: This assumes all images have the same size!
gen_measure_rectangle2 (TmpCtrl_Row, TmpCtrl_Column, TmpCtrl_Phi, TmpCtrl_Len1, TmpCtrl_Len2, 988, 1018, 'nearest_neighbor', MsrHandle_Measure_03_0)
* Measure 03: ***************************************************************
* Measure 03: * The code which follows is to be executed once / measurement *
* Measure 03: ***************************************************************
* Measure 03: The image is assumed to be made available in the
* Measure 03: variable last displayed in the graphics window
copy_obj (Image, Image, 1, 1)
* Measure 03: Execute measurements
measure_pairs (Image, MsrHandle_Measure_03_0, 1, AmplitudeThreshold, 'all', 'all', Row1_Measure_03_0, Column1_Measure_03_0, Amplitude1_Measure_03_0, Row2_Measure_03_0, Column2_Measure_03_0, Amplitude2_Measure_03_0, Width_Measure_03_0, Distance_Measure_03_0)
* Measure 03: Do something with the results

gen_cross_contour_xld (Cross1, Row1_Measure_03_0, Column1_Measure_03_0, 16, 0.785398)
gen_cross_contour_xld (Cross2, Row2_Measure_03_0, Column2_Measure_03_0, 16, 0.785398)

measure_pairs与measure_pos的区别：一般，measure_pairs可以用于许多组边缘对的情况，measure_pos用于一组边缘对的情况。

translate_measure( : : MeasureHandle, Row, Column )（选用）
名字：转换一个度量对象
描述：一般用于一个程序中有很多测量矩形的情况，当使用第二个测量矩形时，不需要重新   gen_measure_rectangle2生成，将第二个测量矩形的中心坐标放到该算子的第二、三个参数当中即可，其第一个参数得到的句柄就相当于使用gen_measure_rectangle2算子正常生成的测量矩形句柄。然后使用measure_pos对该句柄进行正常计算。
参数：
MeasureHandle：测量句柄
Row：新参考点的行坐标
Column ：新参考点的列坐标

4、显示

gen_contour_polygon_rounded_xld创建带圆角的多边形轮廓，坐标和圆角可以通过数组的形式指定。



gen_contour_polygon_xld创建不带圆角的多边形轮廓，坐标同样可以使用数组的形式指定。
Image (input_object) 　　单通道图像  要获取灰度值的图像。
Contour (input_object) 　　以位置坐标输入的XLD轮廓。
Interpolation (input_control) 　插值方法
Grayval (output_control) 所选图像坐标的灰度值。

* fuse.hdev: measuring the width of a fuse wire
* 
dev_update_window ('off')
dev_close_window ()
* ****
* step: acquire image
* ****
read_image (Fuse, 'fuse')
get_image_size (Fuse, Width, Height)
dev_open_window_fit_image (Fuse, 0, 0, Width, Height, WindowID)
set_display_font (WindowID, 12, 'mono', 'true', 'false')
dev_set_draw ('margin')
dev_set_line_width (3)
dev_display (Fuse)
set_display_font (WindowID, 12, 'mono', 'true', 'false')
disp_continue_message (WindowID, 'black', 'true')
stop ()
* ****
* step: create measure object
* ****
* -> specify ROI
Row := 297
Column := 545
Length1 := 80
Length2 := 10
Angle := rad(90)
*
gen_rectangle2 (ROI, Row, Column, Angle, Length1, Length2)
* -> create measure object
*生成一个测量的卡尺
*gen_measure_rectangle2：确定测量的矩形的具体位置
*Row (input_control)：矩形中心点的行坐标
*Column (input_control)：矩形中心点的列坐标
*Phi (input_control)：刨分线与水平方向的夹角（弧度制）
*Length1 (input_control)：矩形长轴的一半
*Length2 (input_control)：矩形短轴的一半
*Width (input_control) ：待处理图像的宽度
*Height (input_control) ：待处理图像的高度
*Interpolation (input_control) ：插值方式（‘bicubic’, ‘bilinear’,‘nearest_neighbor’）
*MeasureHandle (output_control) ：测量对象句柄
gen_measure_rectangle2 (Row, Column, Angle, Length1, Length2, Width, Height, 'bilinear', MeasureHandle)
dev_display (ROI)
disp_continue_message (WindowID, 'black', 'true')
stop ()
* ****
* step: measure  开始测量
* ****‘




* 提取垂直于矩形或者是弧形的直边对
* 单通道的图像
* 上面定义的测量句柄
* 高斯模糊的Sigma的值，也就是桌标准差  ，Sigma越大图像越平缓，高斯函数（正太分布）
* 最小边缘幅度值，越大则检测到的边就越少，和canny算子的那个滞后阈值处理一样理解
* 边缘如何成对，'negative'   postive  :沿着 刨分线的方向由暗到亮维为正     all:
* 选择找点的模式（all： 所有的点，first 输出所有的点， last 输出最后一个点）
* 边缘对第一条边的中心行的坐标（2个值）
* 边缘对第一条边列的坐标
* 两条边的边缘幅度值，有符号的
* 边缘对第二条边的中心行的坐标（2个值）
* 边缘对第二条边列的坐标
* 两条边的边缘幅度值，有符号的


***  边缘对内部之间的距离
***  连续边缘对之间的距离
measure_pairs (Fuse, MeasureHandle, 1, 1, 'negative', 'all', RowEdgeFirst, ColumnEdgeFirst, AmplitudeFirst, RowEdgeSecond, ColumnEdgeSecond, AmplitudeSecond, IntraDistance, InterDistance)




disp_continue_message (WindowID, 'black', 'true')
stop ()
* ****
* step: visualize results
* ****
num :=|RowEdgeFirst|  // 边缘对的个数

for i := 0 to |RowEdgeFirst| - 1 by 1
    
    * gen_contour_polygon_xld创建不带圆角的多边形轮廓
    gen_contour_polygon_xld (EdgeFirst, [-sin(Angle + rad(90)) * Length2 + RowEdgeFirst[i],-sin(Angle - rad(90)) * Length2 + RowEdgeFirst[i]], [cos(Angle + rad(90)) * Length2 + ColumnEdgeFirst[i],cos(Angle - rad(90)) * Length2 + ColumnEdgeFirst[i]])
    gen_contour_polygon_xld (EdgeSecond, [-sin(Angle + rad(90)) * Length2 + RowEdgeSecond[i],-sin(Angle - rad(90)) * Length2 + RowEdgeSecond[i]], [cos(Angle + rad(90)) * Length2 + ColumnEdgeSecond[i],cos(Angle - rad(90)) * Length2 + ColumnEdgeSecond[i]])
    dev_set_color ('red')
    dev_display (EdgeFirst)
    dev_set_color ('magenta')
    dev_display (EdgeSecond)
    dev_set_color ('blue')
    if (i == 0)
        set_tposition (WindowID, RowEdgeFirst[i] + 5, ColumnEdgeFirst[i] + 20)
    else
        set_tposition (WindowID, RowEdgeFirst[i] - 40, ColumnEdgeFirst[i] + 20)
    endif
    write_string (WindowID, 'width: ' + IntraDistance[i] + ' pix')
endfor
disp_continue_message (WindowID, 'black', 'true')
stop ()
* ****
* step: destroy measure object
* ****
close_measure (MeasureHandle)
dev_update_window ('on')
dev_clear_window ()

measure_pin.dev