Applying Discrete Cosine Transform and Grey Relational Analysis to Surface Defect Detection of LEDs

應用離散餘旋轉換與灰關聯分析於發光二極體之表面細微瑕疵檢測

10.29977/JCIIE.200711.0003

林宏達(Hong-Dar Lin)；江軍達(Jun-Dar Jiang)

LED封裝 ； 瑕疵檢測 ； 離散餘弦轉換 ； 灰關聯分析 ； 不均勻照明 ； LED encapsulations ； tiny defect detection ； discrete cosine transform DCT ； gray relational analysis GRA ； uneven illumination

工業工程學刊

24卷6期（2007 / 11 / 01）

458 - 467

英文

發光二極體(Light Emitting Diode; LED)由於具有低能耗、高效率、與長壽命的特性，已廣泛使用於現代化電子產品。但是細微瑕疵經常發生在LED的表面封裝上，不僅影響產品外觀也影響發光強度進而損害產品功能。本研究提出使用自動化視覺系統檢測LED之表面瑕疵，為清楚拍攝LED表面瑕疵，視覺系統必須同時依賴LED自主光源與外部光源的輔助擷取影像，此方式對非擴散型LED的表面會產生照明不均勻現象，增加檢測其表面細微瑕疵的困難度。本研究應用二維離散餘弦轉換(Discrete Cosine Transformation; DCT)將空間域數位影像轉換至離散餘弦頻率域，並結合灰色理論中灰關聯分析(Grey Relational Analysis)技術偵測具較大能量之頻率值位置並將其移除，再還原至空間域，藉由減弱照明不均勻現象的影響突顯空間域影像中的細微瑕疵。最後使用簡單的閥值切割方法即可偵測出細微瑕疵的位置。實驗結果顯示，本研究所提方法之瑕疵面積偵測率可高達95%、瑕疵面積誤判率只有0.03%，遠優於其他方法。

Light-emitting diodes (LEDs), owing to their lower power requirements, higher efficiency, and longer lifetimes, are widely used in modern electronic devices. Nevertheless, tiny defects that often appear in the surface of LEDs impair not only their appearances but also their functions. This paper proposes a global approach for the automated visual inspection of tiny surface defects in non-diffused LED encapsulations. The proposed method, taking advantage of the discrete cosine transform (DCT) and grey relational analysis techniques, overcomes the difficulties of inspecting tiny defects on uneven illumination images of LEDs. We apply the grey relational analysis to the frequency components in the DCT domain, and select the large-magnitude frequency components that represent the background texture of the surface. Then, by reconstructing the frequency matrix without the selected frequency values, we eliminate not only random texture but also uneven illumination patterns and retain anomalies in the restored image. Experimental results demonstrate the effectiveness of the proposed method in inspecting tiny defects in non-diffused LED surfaces.

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