边缘缺陷检测

 *选择待检测边缘
      select_obj(UnionContours, ObjectSelected, Index)
      *平滑边缘
      smooth_contours_xld (ObjectSelected, SmoothedContours, 89)
      *阈值公差
      disTH := 5
      *用于保存缺陷边缘X坐标
      flawPtsX :=[] 
      *用于保存缺陷边缘Y坐标
      flawPtsY :=[]
      *得到待检测边缘点坐标
      get_contour_xld(ObjectSelected, Row2, Col2)
      *待检测边缘上点到平滑边缘的距离
      tuple_length(Row2, Length)
      for Index1 := 0 to Length-1 by 1
          distance_pc(SmoothedContours, Row2[Index1], Col2[Index1], DistanceMin, DistanceMax)
          *根据公差判断是否合格
          if(DistanceMin > disTH)
              flawPtsX :=[flawPtsX,Col2[Index1]]
              flawPtsY :=[flawPtsY,Row2[Index1]]
          endif
      endfor      
      *将缺陷点生成区域，并进一步筛选
      gen_region_points(Region1, flawPtsY, flawPtsX)
      dilation_circle(Region1, RegionDilation, 5)
      connection(RegionDilation, ConnectedRegions1)
      select_shape(ConnectedRegions1, SelectedRegions1, 'area', 'and', 200, 99999)
      gen_empty_obj(EmptyObject)
      count_obj(SelectedRegions1, Number1)
      *再从筛选后的区域，选择不合格的边缘
      for Index1 := 1 to Number1 by 1
          select_obj(SelectedRegions1, ObjectSelected2, Index1)
          smallest_rectangle1(ObjectSelected2, Row11, Column11, Row21, Column2)
          clip_contours_xld(ObjectSelected, ClippedContours, Row11, Column11, Row21, Column2)
          concat_obj(EmptyObject, ClippedContours, EmptyObject)        
      endfor
      *连接相邻不合格边缘缺陷
      union_adjacent_contours_xld(EmptyObject, EmptyObject, 50, 1, 'attr_keep')
      
      *合并缺陷
      concat_obj(FlawEdgeObject, EmptyObject, FlawEdgeObject)