基於快速傅利葉變換的瑕疵檢測

• This program demonstrates how to detect small texture

• defects on the surface of plastic items by using the fast

• fourier transform (FFT).

• First, we construct a suitable filter using Gaussian

• filters. Then, the images and the filter are convolved

• by using fast fourier transforms. Finally, the defects

• are detected in the filtered images by using

• morphology operators.

這個程序是通過 FFT 來檢測物體表面的瑕疵。首先，我們要用高斯濾波器來構造一個合適的濾波器。然後，圖像和濾波器通過 FFT 被轉換。最後通過形態學操作在被濾波的圖像上進行檢測。

-

• Initializations

初始化

dev_update_off ()

dev_close_window ()

read_image (Image, ‘plastics/plastics_01’)

get_image_size (Image, Width, Height)

dev_open_window (0, 0, Width, Height, ‘black’, WindowHandle)

set_display_font (WindowHandle, 14, ‘mono’, ‘true’, ‘false’)

dev_set_draw (‘margin’)

dev_set_line_width (3)

dev_set_color (‘red’)

-

• Optimize the fft speed for the specific image size

為特殊圖像尺寸定制 FFT 速度。

optimize_rft_speed (Width, Height, ‘standard’)

-

• Construct a suitable filter by combining two gaussian

• filters

通過 2 個高斯濾波器來構造一個合適的濾波器

Sigma1 := 10.0

Sigma2 := 3.0

gen_gauss_filter (GaussFilter1, Sigma1, Sigma1, 0.0, ‘none’, ‘rft’, Width, Height)

gen_gauss_filter (GaussFilter2, Sigma2, Sigma2, 0.0, ‘none’, ‘rft’, Width, Height)

sub_image (GaussFilter1, GaussFilter2, Filter, 1, 0)

-

• Process the images iteratively

重複處理圖像

NumImages := 11

for Index := 1 to NumImages by 1

*

• Read an image and convert it to gray values

讀取圖像并轉化為灰度圖像

read_image (Image, 'plastics/plastics_' + Index$'02')

rgb1_to_gray (Image, Image)

• Perform the convolution in the frequency domain

在頻率域生成捲積

rft_generic (Image, ImageFFT, 'to_freq', 'none', 'complex', Width)

convol_fft (ImageFFT, Filter, ImageConvol)

rft_generic (ImageConvol, ImageFiltered, 'from_freq', 'n', 'real', Width)

*

• Process the filtered image

處理被濾波圖像

gray_range_rect (ImageFiltered, ImageResult, 11, 11)

min_max_gray (ImageResult, ImageResult, 0, Min, Max, Range)

threshold (ImageResult, RegionDynThresh, max([5.55,Max * 0.8]), 255)

connection (RegionDynThresh, ConnectedRegions)

select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 4, 99999)

union1 (SelectedRegions, RegionUnion)

closing_circle (RegionUnion, RegionClosing, 10)

connection (RegionClosing, ConnectedRegions1)

select_shape (ConnectedRegions1, SelectedRegions1, 'area', 'and', 10, 99999)

area_center (SelectedRegions1, Area, Row, Column)

*

• Display the results

顯示結果

dev_display (Image)

Number := |Area|

if (Number)

    gen_circle_contour_xld (ContCircle, Row, Column, gen_tuple_const(Number,30), gen_tuple_const(Number,0), gen_tuple_const(Number,rad(360)), 'positive', 1)

    ResultMessage := ['Not OK',Number + ' defect(s) found']

    Color := ['red','black']

    dev_display (ContCircle)

else

    ResultMessage := 'OK'

    Color := 'forest green'

endif

disp_message (WindowHandle, ResultMessage, 'window', 12, 12, Color, 'true')

if (Index != NumImages)

    disp_continue_message (WindowHandle, 'black', 'true')

    stop ()

endif

endfor