液晶面板Mura瑕疵偵測之研究

A Study of Mura Defect Detection on LCD Panels

陳麒遠(Chi-Yuen Chen)

指導教授 ： 洪文斌

淡江大學/工學院/資訊工程學系碩士班/碩士(2011年)

https://doi.org/10.6846/TKU.2011.00411

摘要

薄膜液晶螢幕顯示器為現今主流的數位設備輸出顯示所使用的介面，因為它輕薄、消耗功率低、解析度強、等等優點，所以被大量採用。在生產面板過程中，可能會在面板上產生不均勻的亮暗點，即為瑕疵的地方，在檢測瑕疵點上，目前還是以人工檢測為主，需要依靠大量的人力，以及因為主觀造成的不穩定偵測標準，也帶來面板生產效能的受限，若能架構自動化偵測系統，可以減少人力，也可以穩定偵測的標準，進而提升生產效能。
　　在這篇論文中，目的在於設計液晶螢幕上不均勻亮暗點(MURA)自動偵測的方法，進而應用在液晶螢幕生產線上的自動檢測系統。
　　通常MURA並不是很容易被直接發現，或是訊號太弱較難直接用有效率的方法去偵測到。所以此篇論文提出，利用影像處理的方法，加強瑕疵點與影像背景的對比，進而偵測出瑕疵點的區域。

關鍵字

斑 ； 面板檢測 ； 邊緣偵測 ； 高斯模糊 ； 自動光學檢測

並列摘要

Panel in the production process, it may be non-uniform on the panel points of light and dark, where is the flaw. On the detection of defects, mainly based on manual inspection currently, it need to rely on a large number of human, and because of the instability caused by the subjective standard detection, it also brings the performance of limited panel production, if automatic detection system architecture, it can reduce the human, and detect the standard stable, thus enhance the production efficiency. In this paper, purpose is to design non-uniform light LCD screen dark spot (MURA) method automatically detects, and then used in LCD production line automatic inspection system. This paper presents, using image processing methods, point defects and the background to enhance the image contrast, thus the use of edge detection methods to detect defects in point of the region.

並列關鍵字

MURA ； LCD Inspection ； Edge Detection ； Gaussian Blur ； AOI

參考文獻

[2] 張頌榮，TFT-LCD面板之點線瑕疵自動化檢測系統，國立成功大學電資學院製造工程研究所碩士論文，台灣，2005

[5] Xin Bi, Chungang Zhuang, and Han Ding, “A New Mura Defect Inspection Way for TFT-LCD Using Level Set Method,” In IEEE Signal Processing Letters, Vol. 16, No. 4, Apr. 2009, pages 311-314.

[6] You-Ching Lee, Cheng-En Shie, Din-Chang Tseng, “LCD Mura Detection Based on Accumulated Differences and Multi-resolution Background Subtraction,” ICIG, 2009, 189-194.

[7] Chi-Hao Yeh and Ful-Chiang Wu, “An Image Enhancement Technique in Inspecting Visual Defects of Polarizers in TFT-LCD Industry,” International Conference on Computer Modeling and Simulation 2009 (ICCMS 2009, Macau), (EI)

[8] W. C. Li and D. M. Tsai, “Defect inspection in low-contrast LCD images using Hough transform-based nonstationary line detection,” IEEE Transactions on Industrial Informatics, Vol. 7, 2011, pp. 136-147, (SCI)