本研究應用數位影像處理的技術於偏光板(Polarizer)產品瑕疵檢測。首先利用線掃瞄(Line Scan)電荷耦合元件(Charged Couple Device, CCD)擷取瑕疵影像，將尺寸大小為 像素(Pixel)的瑕疵影像利用降幅抽樣壓縮法(Downsampling Compression)縮小4倍，再利用小波轉換(Wavelet Transform, WT) 將降幅抽樣壓縮法縮小4倍的影像經2次小波轉換再縮小16倍，此時影像的大小為 像素，也成為後續影像處理所運算的影像尺寸。然後利用乘冪律轉換(Power-law Transform)來強化瑕疵特徵的資訊，接著對影像進行低階高位中間(Lower-Upper-Middle, LUM)濾波器，除了可以去除背景的雜訊，同時可以保留瑕疵的邊緣特性。再利用拉普拉斯(Laplace)運算子之對45度和90度增量旋轉有等方性結果的遮罩找出瑕疵的邊緣，接著利用統計式(Statistical)門檻值決定法將瑕疵影像分割出來，最後利用霍夫轉換(Hough Transform)區分灰塵、異物、打痕和氣泡的點類瑕疵(Spot Defect)與刮痕的直線類瑕疵(Line Defect)。本研究擷取的200張偏光板瑕疵影像，經由自行研發的檢測系統測試，從實驗結果可明顯看出，可將接受測試的200張影像之瑕疵全數檢測出來，並成功的區分點類瑕疵及直線類瑕疵，其區分率為100%，且平均檢測一張影像只需要0.9秒左右，因此說明本研究已成功發展出一套適合應用於偏光板的線上即時(On-line Real time)瑕疵檢測系統。
本研究研製的偏光板自動化光學檢測(Automatic Optical Inspection, AOI)系統，可以改善克服目前以人工檢測所帶來不便和誤判，並立即告知生產者偏光板出現之缺陷為製程中所產生的點類瑕疵，或者是後續搬運過程中所造成的直線類瑕疵，讓生產者能在不同瑕疵出現情況下進行不同的改善。

This research applied digital image processing technology to the defect inspection of polarizer products. It first used line scan charged couple device (CCD) to screen the defect images, and then reduced the defect image ( pixel) to four times smaller using downsampling compression method, and then conducted the Wavelet transform (WT) on the four times smaller image for two times to reduce the size to 16 times smaller, and then the image size was pixel, so that it became the right size for the following image processing. Then the power-law transform was used to intensify the characteristics of the defect, and then processed it with lower-upper-middle (LUM) filter which could delete noise background while reserve the edge characteristics of the defect. And then the edge of the defect would be found out through the screening of the isotropic results after 45 degrees and 90 degrees increment of Laplace operator, and then used the statistic threshold method to separate the defect image, and in the end used Hough transform to distinguish the spot defect as dust, foreign matter and beat print, air bubble, and the line defect as scratch mark. This research picked out 200 sheets of polarizer defect images, then it investigated them by self-developed inspection system, the experimental result showed that it could test all the flaws on the 200 sheets of images, and successfully distinguished the spot defect and line defect, the distinguish rate is 100%, and it only cost 0.9 sec to detect a sheet. Therefore it has clear that this research has successfully developed a set of on-line real time defect inspection system applicable to the polarizer.
The polarizer automatic optical inspection (AOI) system developed by this research could overcome the inconveniences and misjudgments caused by the manual inspection, and it would inform the producers whether the defect on the polarizer was spot defect formed in the manufacture or line defect in the following transportation, so that the producers could make different improvements for different types of defects.

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