少有人走的路处理要求
椭圆/圆环（产品易变形，为椭圆）内外圆毛刺（凸起）缺口（凹陷）检测。
处理方法1
方法一思路
1、这是一个圆环产品检测，我们可以通过产品区域与标准圆环进行比较得出不良区域。
2、为了避免误检、误判，我们可以通过区域筛选阈值偏移的方法滤除干扰区域，可以将标准圆环放大消除一些圆度导致干扰。
3、根据不同用户的精度要求，可以通过调节缺陷面积进行筛选。
4、方法1的代码量有点多，但是更贴近工业现场使用。
方法一halcon源码
dev_close_window ()read_image (Image, 'C:/Users/22967/Desktop/圆环缺陷检测/处理1.jpg')dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)dev_display (Image)*********************方法一*******************************变量定义* 卡尺测量参数CenterRow:=0CenterColumn:=0CenterRadius:=0* 灰度分割阈值偏移ThresholdOffest:=80* 缺陷区域面积阈值NGArea:=50*圆环内外偏移阈值RadiusOffest:=5* Image Acquisition 01: Code generated by Image Acquisition 01list_files ('C:/Users/22967/Desktop/圆环缺陷检测', ['files','follow_links'], ImageFiles)tuple_regexp_select (ImageFiles, ['\\.(tif|tiff|gif|bmp|jpg|jpeg|jp2|png|pcx|pgm|ppm|pbm|xwd|ima|hobj)$','ignore_case'], ImageFiles)for Index := 0 to |ImageFiles| - 1 by 1
read_image (Image, ImageFiles[Index])
rgb1_to_gray (Image, GrayImage)
*****圆环灰度筛选
binary_threshold (GrayImage, Region, 'max_separability', 'dark', UsedThreshold)
threshold (GrayImage, Region1, 0, UsedThreshold+ThresholdOffest)
*分割连通域
connection (Region1, ConnectedRegions)
*选取圆环区域
select_shape_std (ConnectedRegions, SelectedRegions, 'max_area', 70)
*滤除圆环边缘毛刺
opening_circle (SelectedRegions, RegionOpening, 1.5)
*****求圆环内外圆
*求圆环外圆
smallest_circle (RegionOpening, Row, Column, Radius)
CenterRow[0]:=Row
CenterColumn[0]:=Column
CenterRadius[0]:=Radius
*求圆环内圆
fill_up (RegionOpening, RegionFillUp)
difference (RegionFillUp, RegionOpening, RegionDifference)
connection (RegionDifference, ConnectedRegions2)
select_shape_std (ConnectedRegions2, SelectedRegions1, 'max_area', 70)
smallest_circle (SelectedRegions1, Row1, Column1, Radius1)
CenterRow[1]:=Row1
CenterColumn[1]:=Column1
CenterRadius[1]:=Radius1
*****对内外圆进行卡尺测量
*创建测量句柄
create_metrology_model (MetrologyHandle)
*设置卡尺测量参数
add_metrology_object_circle_measure (MetrologyHandle, CenterRow, CenterColumn, CenterRadius, CenterRadius[0]/10, CenterRadius[0]/60, 1, 4, ['measure_distance','min_score'], [CenterRadius[0]/30,0.2], Indexnumb)
*进行测量
apply_metrology_model (Image, MetrologyHandle)
*得到测量结果
get_metrology_object_result (MetrologyHandle, 'all', 'all', 'result_type', 'all_param', Parameter)
get_metrology_object_result_contour (Contour, MetrologyHandle, 'all', 'all', 1.5)
get_metrology_object_measures (Contours, MetrologyHandle, 'all', 'all', Row1, Column1)
*****求出标准圆环,进行缺陷检测
*突出部分
gen_circle (Circle, Parameter[0], Parameter[1], Parameter[2]+RadiusOffest)
gen_circle (Circle1, Parameter[3], Parameter[4], Parameter[5]-RadiusOffest)
difference (Circle, Circle1, RegionDifference1)
difference (SelectedRegions, RegionDifference1, RegionDifference2)
*内凹部分
gen_circle (Circle2, Parameter[0], Parameter[1], Parameter[2]-RadiusOffest)
gen_circle (Circle3,Parameter[3], Parameter[4], Parameter[5]+RadiusOffest)
difference (Circle2, Circle3, RegionDifference4)
difference (RegionDifference4, SelectedRegions, RegionDifference3)
*滤除噪点
opening_circle (RegionDifference2, RegionOpening1, 1.5)
opening_circle (RegionDifference3, RegionOpening2, 1.5)
*合并缺陷区域
union2 (RegionOpening1, RegionOpening2, RegionUnion)
closing_circle (RegionUnion, RegionClosing, 3.5)
connection (RegionClosing, ConnectedRegions1)
*结果判断
area_center (ConnectedRegions1, Area, Row2, Column2)
count_obj (ConnectedRegions1, Number)
gen_empty_obj (EmptyObject)
for Index1 := 1 to Number by 1
if (Area[Index1-1] > NGArea)
select_obj (ConnectedRegions1, ObjectSelected, Index1)
smallest_circle (ObjectSelected, Row3, Column3, Radius2)
gen_circle (Circle4, Row3, Column3, Radius2)
concat_obj (EmptyObject, Circle4, EmptyObject)
endif
endfor
dev_set_draw ('margin')
dev_set_line_width (3)
dev_display (Image)
dev_display (EmptyObject)* stop()处理效果
处理方法2
方法二思路
1、利用形态学方法进行缺陷检测。
2、缺点就是对圆度不敏感。
方法二halcon源码
dev_close_window ()read_image (Image, 'C:/Users/22967/Desktop/圆环缺陷检测/处理1.jpg')dev_open_window_fit_image (Image, 0, 0, -1, -1, WindowHandle)dev_display (Image)*********************方法二*************************** 灰度分割阈值偏移ThresholdOffest:=80*外圆缺陷查找阈值OutCircleTh:=200.5*内圆缺陷查找阈值InCircleTh:=100.5*缺陷区域面积阈值NGArea:=50*噪点过滤阈值DelNoise:=1.5* Image Acquisition 01: Code generated by Image Acquisition 01list_files ('C:/Users/22967/Desktop/圆环缺陷检测', ['files','follow_links'], ImageFiles)tuple_regexp_select (ImageFiles, ['\\.(tif|tiff|gif|bmp|jpg|jpeg|jp2|png|pcx|pgm|ppm|pbm|xwd|ima|hobj)$','ignore_case'], ImageFiles)for Index := 0 to |ImageFiles| - 1 by 1
*读入图片
read_image (Image, ImageFiles[Index])
rgb1_to_gray (Image, GrayImage)
*二值化选取垫片区域
binary_threshold (GrayImage, Region, 'max_separability', 'dark', UsedThreshold)
threshold (GrayImage, Region1, 0, UsedThreshold+ThresholdOffest)
connection (Region1, ConnectedRegions)
select_shape_std (ConnectedRegions, SelectedRegions, 'max_area', 70)
*外圆缺陷查找
fill_up (SelectedRegions, RegionFillUp1)
opening_circle (RegionFillUp1, RegionOpening, OutCircleTh)
difference (RegionFillUp1, RegionOpening, RegionDifference5)
*内圆缺陷查找
difference (RegionFillUp1, SelectedRegions, RegionDifference6)
connection (RegionDifference6, ConnectedRegions3)
select_shape_std (ConnectedRegions3, SelectedRegions2, 'max_area', 70)
opening_circle (SelectedRegions2, RegionOpening3, InCircleTh)
difference (SelectedRegions2, RegionOpening3, RegionDifference7)
*合并缺陷区域
union2 (RegionDifference5, RegionDifference7, RegionUnion1)
opening_circle (RegionUnion1, RegionOpening4, DelNoise)
connection (RegionOpening4, ConnectedRegions4)
*结果判断
area_center (ConnectedRegions4, Area1, Row4, Column4)
gen_empty_obj (EmptyObject1)
for Index1 := 1 to |Area1| by 1
if (Area1[Index1-1] > NGArea)
select_obj (ConnectedRegions4, ObjectSelected, Index1)
smallest_circle (ObjectSelected, Row3, Column3, Radius2)
gen_circle (Circle4, Row3, Column3, Radius2)
concat_obj (EmptyObject1, Circle4, EmptyObject1)
endif
endfor
*显示结果
dev_set_draw ('margin')
dev_set_line_width (3)
dev_display (Image)
dev_display (EmptyObject1)
stop()处理效果
转载自：
https://blog.csdn.net/cashmood/article/details/109637419
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