核酸管外观缺陷检测(一)

1.1 应用示例思路

(1) 对核酸管图像进行灰度化、阈值分割和连通域分析；

(2) 筛选出待检测的区域，并对该区域进行变换校正；

(3) 进一步获取待检测的ROI区域，并根据几何特征和阈值条件，来对核酸管外观进行检测；

(4) 将检测结果写入txt文档。

1.2 应用示例代码

*统计核酸管外观正常的数组
P_Tuple:=[]
*统计核酸管外观缺陷的数组
N_Tuple:=[]
*判断文件是否存在
file_path:= './核酸管外观缺陷检测统计1.txt'
file_exists (file_path, file_exist)
if (file_exist==1)delete_file (file_path)
endif
open_file (file_path, 'output', FileHandle)
*获取文件路径列表
list_files ('./Test_img/', ['files','follow_links'], ImageFiles)
*文件筛选
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 1img_path:=ImageFiles[Index]*img_path:='./Test_img/Image_20230420091226458.bmp'*文件名拆分parse_filename (img_path, BaseName, Extension, Directory)*读取核酸管图片read_image (Image, img_path)*灰度化rgb1_to_gray (Image, GrayImage)*阈值分割threshold (GrayImage, Region, 30, 145)*填充孔洞fill_up (Region, RegionFillUp)*连通区域分析connection (RegionFillUp, ConnectedRegions)*获取面积area_center (ConnectedRegions, Area, Row, Column)*通过面积筛选区域select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 500000, 800000)*获取区域外接矩形smallest_rectangle2 (SelectedRegions, Row1, Column1, Phi, Length1, Length2)*创建变换模型vector_angle_to_rigid (Row1, Column1, abs(Phi), Row1, Column1, acos(0.0), HomMat2D)*进行区域变换affine_trans_region (SelectedRegions, RegionAffineTrans, HomMat2D, 'nearest_neighbor')*获取区域外接矩形(平行于坐标轴)smallest_rectangle1 (RegionAffineTrans, Row11, Column11, Row12, Column12)*裁剪区域clip_region (RegionAffineTrans, RegionClipped1, Row11, Column12-200, Row12, Column12)*获取区域外接矩形(平行于坐标轴)smallest_rectangle1 (RegionClipped1, Row21, Column21, Row22, Column22)*裁剪区域clip_region (RegionClipped1, RegionClipped2, int((Row21+Row22)/2.0)-20, Column12-200, int((Row21+Row22)/2.0)+20, Column12)*获取区域外接矩形(平行于坐标轴)smallest_rectangle1 (RegionClipped2, Row31, Column31, Row32, Column32) distance:=Column32-Column31if(distance>=180)dev_clear_window ()get_image_size (Image, Width, Height)dev_open_window (0, 0, Width/2, Height/2, 'black', WindowHandle)dev_display (Image)*设置颜色dev_set_color ('green')*显示字符set_tposition (WindowHandle, 10, 5)  //设置文本光标1的位置write_string (WindowHandle, '核酸管外观正常！')set_tposition (WindowHandle, 50, 5)  //设置文本2光标的位置write_string (WindowHandle, ['核酸管外观正常的图片名：',BaseName])dev_close_window ()P_Tuple:=[P_Tuple,1]fwrite_string(FileHandle,[Index,'核酸管外观正常的图片名：',BaseName])fnew_line(FileHandle)    elsedev_clear_window ()get_image_size (Image, Width, Height)dev_open_window (0, 0, Width/2, Height/2, 'black', WindowHandle)dev_display (Image)*设置颜色dev_set_color ('green')*显示字符set_tposition (WindowHandle, 10, 5)  //设置文本光标1的位置write_string (WindowHandle, '核酸管外观有缺陷！')set_tposition (WindowHandle, 50, 5)  //设置文本2光标的位置write_string (WindowHandle, ['核酸管外观缺陷的图片名：',BaseName])dev_close_window ()N_Tuple:=[N_Tuple,0]fwrite_string(FileHandle,[Index,'核酸管外观缺陷的图片名：',BaseName])fnew_line(FileHandle)    endif
endfortuple_length (P_Tuple, P_Length)
tuple_length (N_Tuple, N_Length)
Yield_Rate:= real(P_Length)/real(N_Length+P_Length)
fwrite_string(FileHandle,['核酸管良品率：',Yield_Rate])
fnew_line(FileHandle)
close_file (FileHandle)

1.3 结果展示

(1) 单张图片检测结果：

 (2) 部分图片检测结果：