• Halcon学习:缺陷检测


    通过拟合来求缺陷,对应halcon例程:方法—》轮廓线处理—》fit_rectangle2_contour_xld.hdev。

     1 read_image (Image, 'C:/Users/zx80-165/Desktop/111.jpg')
     2 get_image_size (Image, Width, Height)
     3 dev_open_window (0, 0, Width, Height, 'black', WindowHandle)
     4 rgb1_to_gray (Image, GrayImage)
     5 dev_display (GrayImage)
     6 *快速二值化,与二值化是一致的,只不过多加了个参数,最后一个参数
     7 *是保留臭臭泥大于该值的二值化区域,否则还要调用一个select_shape
     8 fast_threshold (GrayImage, Region, 128, 255, 10)
     9 
    10 *利用形态学提取边界
    11 boundary (Region, RegionBorder, 'inner')
    12 *膨胀,用矩形结构元素进行膨胀
    13 dilation_rectangle1 (RegionBorder, RegionDilation, 7, 7)
    14 *截取边缘图像
    15 reduce_domain (GrayImage, RegionDilation, ImageReduced)
    16 
    17 *提取亚像素轮廓(canny边缘检测),1.7为平滑系数
    18 edges_sub_pix (ImageReduced, Edges, 'canny', 1.7, 40, 120)
    19 select_shape_xld (Edges, SelectedXLD, 'contlength', 'and', 199.45, 1000)
    20 count_obj (SelectedXLD, Number)
    21 
    22 *用最小外接矩形你和该亚像素轮廓
    23 fit_rectangle2_contour_xld (SelectedXLD, 'regression', -1, 0, 0, 3, 2, Row, Column, Phi, Length1, Length2, PointOrder)
    24 dev_set_draw ('margin')
    25 *生成拟合的亚像素矩形轮廓
    26 gen_rectangle2_contour_xld (Rectangle, Row, Column, Phi, Length1, Length2)
    27 dev_display (Rectangle)
    28 
    29 set_display_font (WindowHandle, 16, 'mono', 'true', 'false')
    30 dev_display (GrayImage)
    31 for i := 0 to Number-1 by 1
    32     *依次提取途中的亚像素轮廓
    33     select_obj (SelectedXLD, ObjectSelected, i+1)
    34     *获取亚像素轮廓每一个点的坐标
    35     get_contour_xld (ObjectSelected, Rows, Cols)
    36     gen_rectangle2_contour_xld (Rectangle2, Row[i], Column[i], Phi[i], Length1[i], Length2[i])  
    37     get_contour_xld (Rectangle2, Row1, Col)
    38     *计算轮廓上每一个点到拟合矩形四个角点的最小距离,对四周的点比较宽松,如果在拟合隽星以角点为圆心,
    39     *半径为7的圆内,认为是正常的,对于边缘比较严格,如果某点离其拟合矩形对应点之间的距离大于1则认为有缺陷
    40     D1:=sqrt((Rows-Row1[0])*(Rows-Row1[0])+(Cols-Col[0])*(Cols-Col[0]))
    41     D2:=sqrt((Rows-Row1[1])*(Rows-Row1[1])+(Cols-Col[1])*(Cols-Col[1]))
    42     D3:=sqrt((Rows-Row1[2])*(Rows-Row1[2])+(Cols-Col[2])*(Cols-Col[2]))
    43     D4:=sqrt((Rows-Row1[3])*(Rows-Row1[3])+(Cols-Col[3])*(Cols-Col[3]))
    44     DistConor:=min2(min2(D1,D2),min2(D3,D4))
    45     *计算轮廓上每一点与其拟合矩形对应点之间的距离
    46     dist_rectangle2_contour_points_xld (ObjectSelected, 0, Row[i], Column[i], Phi[i], Length1[i], Length2[i], Distances)
    47     
    48     flag :=true
    49     for j := 0 to |Distances|-1 by 1
    50         if(DistConor[j]>7 and Distances[j]>1)
    51             flag:=false
    52             break
    53         endif
    54     endfor
    55     if(flag)
    56         disp_message (WindowHandle, 'OK', 'image', Row[i], Column[i]- Length2[i]/2, 'green', 'true')
    57     else
    58         disp_message (WindowHandle, 'Not OK', 'image', Row[i], Column[i]- Length2[i]/2, 'red', 'true')
    59     endif
    60 endfor

    效果图:

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  • 原文地址:https://www.cnblogs.com/zxl971213/p/13722578.html
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