基于原始海报担心位置移动，我发布了另一个涉及更多的答案。对于这种情况，这种策略可能不是最简单的，但它是一种适用于很多情况的通用策略。通常，此类问题的解决方法如下：
1) 对零件进行粗略定位。这通常涉及斑点检测或匹配策略（相关性、基于形状等）。此步骤的输出是描述对象位置（平移、方向）的转换。
2) 基于在步骤 1 中找到的位置，用于检测特征（线、孔等）的搜索区域被转换或更新到新的位置。或者整个图像被转换。
我无法发布所有代码，因为它太大了。如果您希望我通过电子邮件将完整的 HDevelop 脚本发送给您，您必须给我发私信。这里有一些片段可以给你一个想法：
第 1 步：设置图像阈值并设置应找到线条的搜索区域。仅发布前两个地区的代码，但其他三个地区的代码相同
threshold(Image, RegionThreshold, 0, 100)
region_to_bin(RegionThreshold, ImageBinary, 255, 0, Width, Height)
dev_display(ImageBinary)
*Use the mouse to draw region 1 around first line. Right click when finished.
draw_rectangle2(WindowHandle, Reg1Row, Reg1Column, Reg1Phi, Reg1Length1, Reg1Length2)
gen_rectangle2(Rectangle1, Reg1Row, Reg1Column, Reg1Phi, Reg1Length1, Reg1Length2)
*Use the mouse to draw region 2 around second line. Right click when finished.
draw_rectangle2(WindowHandle, Reg2Row, Reg2Column, Reg2Phi, Reg2Length1, Reg2Length2)
gen_rectangle2(Rectangle2, Reg2Row, Reg2Column, Reg2Phi, Reg2Length1, Reg2Length2)
搜索区域如下所示：
第二步：计算线的交点。仅发布前两行的代码，但其他三行的代码相同
*get line segment 1
reduce_domain(ImageBinary, Rectangle1, ImageReduced)
edges_sub_pix (ImageReduced, EdgesLine1, 'lanser2', 0.1, 20, 40)
fit_line_contour_xld (EdgesLine1, 'regression', -1, 0, 5, 2, RowBeginLine1, \
ColBeginLine1, RowEndLine1, ColEndLine1, Nr, Nc, Dist)
*get line segment 2
reduce_domain(ImageBinary, Rectangle2, ImageReduced)
edges_sub_pix (ImageReduced, EdgesLine2, 'lanser2', 0.1, 20, 40)
fit_line_contour_xld (EdgesLine2, 'regression', -1, 0, 5, 2, RowBeginLine2, \
ColBeginLine2, RowEndLine2, ColEndLine2, Nr, Nc, Dist)
*Calculate and display intersection line 1 to line 2
intersection_lines(RowBeginLine1, ColBeginLine1, RowEndLine1, ColEndLine1, \
RowBeginLine2, ColBeginLine2, RowEndLine2, ColEndLine2, \
Line1Line2IntersectRow, Line1Line2IntersectCol,
IsOverlappingLine1Line2)
这会产生以下输出：
第 3 步：创建一个归一化互相关模型，用于在对象进行平移或旋转时查找对象。这里我在底部选择一个简单的区域
gen_rectangle1 (ModelRegion, 271.583, 200, 349.083, 530)
reduce_domain (ImageBinary, ModelRegion, TemplateImage)
create_ncc_model (TemplateImage, 'auto', rad(0), rad(360), 'auto', 'use_polarity',
ModelID)
area_center (ModelRegion, ModelRegionArea, RefRow, RefColumn)
输出图像
第 4 步：现在我们考虑移动对象时会发生什么。为了模拟这一点，我使用仿射变换扭曲了图像。然后我搜索了在步骤 3 中创建的标准化互相关模型。您可以在下面看到该对象已找到。输出是找到它的行、列和角度。这被转换为一个名为 AlignmentHomMat2D 的矩阵
部分代码：
threshold(TransImage, RegionThreshold, 0, 100)
region_to_bin(RegionThreshold, ImageBinaryScene, 255, 0, Width, Height)
* Matching 01: Find the model
find_ncc_model (ImageBinaryScene, ModelID, rad(0), rad(360), 0.8, 1, 0.5, 'true', 0,
Row, Column, Angle, Score)
* Matching 01: Display the centers of the matches in the detected positions
dev_display (TransImage)
set_line_width(WindowHandle, 3)
for I := 0 to |Score| - 1 by 1
* Matching 01: Display the center of the match
gen_cross_contour_xld (TransContours, Row[I], Column[I], 20, Angle)
dev_set_color ('green')
dev_display (TransContours)
hom_mat2d_identity (AlignmentHomMat2D)
hom_mat2d_translate (AlignmentHomMat2D, -RefRow, -RefColumn, AlignmentHomMat2D)
hom_mat2d_rotate (AlignmentHomMat2D, Angle[I], 0, 0, AlignmentHomMat2D)
hom_mat2d_translate (AlignmentHomMat2D, Row[I], Column[I], AlignmentHomMat2D)
* Matching 01: Display the aligned model region
affine_trans_region (ModelRegion, RegionAffineTrans, AlignmentHomMat2D,
'nearest_neighbor')
dev_display (RegionAffineTrans)
endfor
输出如下：
第 5 步：最后，根据找到互相关模型的位置更新用于定位原始线的搜索区域。
这是代码。同样，我只显示前两个线段：
*transform initial search regions
affine_trans_region(Rectangle1, Rectangle1Transformed,
AlignmentHomMat2D,'nearest_neighbor')
affine_trans_region(Rectangle2, Rectangle2Transformed,
AlignmentHomMat2D,'nearest_neighbor')
*get line segment 1
reduce_domain(ImageBinaryScene, Rectangle1Transformed, ImageReduced)
edges_sub_pix (ImageReduced, EdgesLine1, 'lanser2', 0.5, 20, 40)
fit_line_contour_xld (EdgesLine1, 'regression', -1, 0, 5, 2, RowBeginLine1, \
ColBeginLine1, RowEndLine1, ColEndLine1, Nr, Nc, Dist)
*get line segment 2
reduce_domain(ImageBinaryScene, Rectangle2Transformed, ImageReduced)
edges_sub_pix (ImageReduced, EdgesLine2, 'lanser2', 0.5, 20, 40)
fit_line_contour_xld (EdgesLine2, 'regression', -1, 0, 5, 2, RowBeginLine2, \
ColBeginLine2, RowEndLine2, ColEndLine2, Nr, Nc, Dist)
*Calculate and display intersection line 1 to line 2
intersection_lines(RowBeginLine1, ColBeginLine1, RowEndLine1, ColEndLine1, \
RowBeginLine2, ColBeginLine2, RowEndLine2, ColEndLine2, \
Line1Line2IntersectRow, Line1Line2IntersectCol,
IsOverlappingLine1Line2)
这会产生以下输出：
