臺灣博碩士論文加值系統

薄膜電晶體液晶顯示器 ( TFT-LCD ) ，近幾年逐漸成為平面顯示器(FPD)產業發展的主流。薄膜電晶體液晶顯示器製造過程中經常因為粉塵或液晶分佈不均勻因而產生Mura瑕疵。Mura瑕疵常具有低對比和非均一性的特質，大部分製造商仍然以人工目檢的方式來檢測薄膜電晶體液晶顯示器的品質，人工目檢的檢測方式成本高，而且無法達到固定之量測品質標準；因此本文基於背景重建的概念，提出一新穎的薄膜電晶體液晶顯示器瑕疵檢測演算法，以達到自動化瑕疵(Mura)檢測的目的。由於液晶顯示器面板上存在著非均一性的亮度變化，且瑕疵與背景間的亮度差異很小，因此造成Mura瑕疵檢測上的困難。利用離散餘弦轉換(DCT)，從離散餘弦係數之反轉換，能有效地淬取出背景資訊，重新建構出不具瑕疵之原始背景影像，解決薄膜電晶體液晶顯示器影像非均一性之檢測問題。由原始瑕疵影像與不含瑕疵的背景影像之相異性，透過適當的閥值選取，可將瑕疵從影像中分割出來。本文提出之Mura瑕疵檢測演算法，已針對多個天然Mura瑕疵影像進行測試，實驗結果證實此演算法對於真實的Mura瑕疵影像，可精確且快速地檢出瑕疵；在平面顯示器(FPD)的線上檢測工程上，將具有實質應用潛力。

An innovative TFT-LCD defect detection algorithm is developed for automatic detection of Mura defects based on Discrete Cosine Transform (DCT) principle for background image reconstruction. Efficient and accurate surface defect detection on FPD panels has never been so important in achieving the high yield rate of FPD manufacturing. All kinds of FPD manufacturers need to inspect products such as screen panels, control PCBs and final assembly modules. Front-of-screen (FOS) quality performed by a human visual inspection is susceptible to unacceptable manufacturing costs and uncertain product delivery time. Therefore, automatic inspection of FOS quality is highly essential to achieve effective defect detection for optimizing operation efficiency and product quality.
One of the visually most difficult recognizing problems in LCD panel inspection is to deal with clearly distinguishing specific regions of low contrast and non-uniform brightness called mura. A mura defect in general processes a non-uniform brightness region that slightly differs from the background by down to unit signal level, where it is detectable only when its size is larger than a specific size. Detecting blob-Mura defects in a LCD panel can be difficult due to non-uniform brightness background and slightly different brightness levels between the defect region and the background. To resolve this issue, a DCT-based background reconstruction algorithm is developed to establish the background image without mixing with the detected object- Mura defects. Based on DCT principle, we present a new segmentation method for detecting area-mura. Through some experimental tests on natural Mura defects, it was verified that the proposed algorithm has a superior capability for detecting blob-mura defects in its detection accuracy and speed.

目錄

中文摘要 i
ABSTRACT ii
誌謝 iv
目錄 v
圖目錄 vii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究範圍與目的 2
1.3 研究方法簡介 5
1.4 論文架構 6
第二章 文獻回顧 7
2.1 薄膜電晶體液晶顯示器簡介 7
2.1.1 薄膜電晶體液晶顯示器原理與構造 8
2.1.2 薄膜電晶體液晶顯示器製造流程 11
2.2 液晶顯示器瑕疵檢測 13
2.3 頻譜分析之瑕疵檢測技術 20
2.3.1 空間域影像分析 21
2.3.2 頻率域影像分析 22
2.4 離散餘弦轉換之應用 25
2.5 瑕疵量化評估之探討 26
2.6 文獻探討結論 29
第三章 數位影像處理技術 30
3.1 影像二值化 30
3.2 影像濾波 32
3.3 影像型態學 35
3.4 以區域為基礎之影像分割 38
第四章 研究方法 40
4.1 研究方法流程概述 40
4.2 離散餘弦轉換技術 44
4.2.1 一維離散餘弦轉換 45
4.2.2 二維離散餘弦轉換 47
4.2.3 二維離散餘弦轉換應用於瑕疵檢測 51
4.3 濾波器設計與最佳化 51
4.3.1 濾波器實驗 53
4.3.2 濾波器設計 58
4.4 瑕疵分割 66
4.4.1 影像二值化 66
4.4.2 影像分割 68
4.5 瑕疵量化與誤判消除 69
第五章 實驗結果與分析 73
5.1 量測系統架構之設計 73
5.1.1 影像之前處理程序 74
5.2 瑕疵量化分析 77
5.3 薄膜電晶體液晶顯示器瑕疵檢測結果 79
5.4 系統效能評估 86
第六章 結論與未來展望 94
6.1 結論 94
6.2 未來發展 95
參考文獻 96

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