halcon极坐标转换与亮暗缺陷检测结合的案例(转)

 3 dev_set_draw ('margin')
 4 dev_set_line_width (2)
 5 set_font (3600, '-Courier New-16-*-*-*-*-1-')
 6 
 7 list_files ('C:/Users/Administrator/Desktop/bottle', ['files','follow_links','recursive'], ImageFiles)
 8 tuple_regexp_select (ImageFiles, ['\.(tif|tiff|gif|bmp|jpg|jpeg|jp2|png|pcx|pgm|ppm|pbm|xwd|ima|hobj)$','ignore_case'], ImageFiles)
 9 
10 for Index := 1 to |ImageFiles| - 1 by 1
11     read_image (Image, ImageFiles[Index])
12     get_image_size (Image, Width, Height)
13     threshold (Image, Region, 0, 60)
14     fill_up (Region, RegionFillUp)
15     opening_circle (RegionFillUp, RegionOpening, 8.5)
16     smallest_circle (RegionOpening, Row0, Column0, Radius0)
17  
18     *下面这个函数是自己写的抓圆的函数，细节不表。你也可以用fit_circle_contour_xld 和 gen_circle_contour_xld实现类似功能
19     find_circle (Image, PartCircleXLD, Regions, Cross, Circle, Row0, Column0, Radius0 + 10, 0, 360, 30, 70, 20, 1, 50, 'negative', 'first', 'inner', 10, 'circle', RowCenter, ColCenter, Radius)
20     dev_display (Image)
21     dev_display (Circle)
22     
23     *该算子对一个图像的圆弧区域进行极坐标变换，圆弧外径是Radius，内径是Radius - 100，即圆弧厚度是100
24     *同理，圆弧展开成矩形后，矩形宽度应该是外弧圆圈的周长，即6.28319 * Radius（周长 = 2π × r） ；矩形高度应该是圆弧厚度，即100
25     polar_trans_image_ext (Image, PolarTransImage, RowCenter, ColCenter, 0, 6.28319, Radius - 100, Radius, 6.28319 * Radius, 100, 'nearest_neighbor')
26     
27     *下面这句仅用于观察image的反向极坐标变换，生成的图片的宽高还是设置为最原始图像的Width, Height
28     polar_trans_image_inv  (PolarTransImage, XYTransImage, RowCenter, ColCenter, 0, 6.28319, Radius - 100, Radius, Width, Height, 'nearest_neighbor')
29     
30     *mean_image选择主要沿水平方向进行模糊，动态阈值的'not_equal'参数同时筛选出了跟周围比过亮和过暗的区域(因为过暗和过亮都是缺陷)
31     mean_image (PolarTransImage, ImageMean, 500, 3)
32     dyn_threshold (PolarTransImage, ImageMean, Region1, 30, 'not_equal')
33     
34     fill_up_shape (Region1, RegionFillUp1, 'area', 1, 100)
35     *开运算去掉细小干扰
36     opening_circle (RegionFillUp1, RegionOpening1, 1.5)
37     connection (RegionOpening1, ConnectedRegions)
38     
39     *之所以要进行极坐标转换，就是为了这里用'height'来筛选，这是本例使用极坐标变换最关键的原因
40     select_shape (ConnectedRegions, SelectedRegions, 'height', 'and', 10, 99999)
41     polar_trans_region_inv (SelectedRegions, XYTransRegion, RowCenter, ColCenter, 0, 6.28319, Radius - 100, Radius, 6.28319 * Radius, 100, Width, Height, 'nearest_neighbor')
42     dev_display (Image)
43     dev_display (XYTransRegion)
44     
45     stop ()

46 endfor

虽然极坐标变换是本例中的核心思路，但是仍有三句非常巧妙的代码，仔细想想为什么这三句代码很巧妙：

31     mean_image (PolarTransImage, ImageMean, 500, 3)
32     dyn_threshold (PolarTransImage, ImageMean, Region1, 30, 'not_equal')

40     select_shape (ConnectedRegions, SelectedRegions, 'height', 'and', 10, 99999)

原文连接 https://www.cnblogs.com/xh6300/p/10406753.html