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研究生： 蘇琬婷
論文名稱： Measurement of multiple JNDs for developing Mura ranking standard in LCD
量測多倍視覺差異對比閾值建立液晶顯示器不均勻現象之分級標準
指導教授： 黃雪玲
口試委員:
學位類別： 碩士
Master
系所名稱： 工學院 - 工業工程與工程管理學系
Department of Industrial Engineering and Engineering Management
論文出版年： 2008
畢業學年度： 96
語文別： 英文
論文頁數： 60
中文關鍵詞： 平面液晶顯示器 、Mura 、自動檢測系統 、JND 、多倍視覺差異對比閾値 、分級
外文關鍵詞： LCD, Mura, automation Mura inspection system, multiple JNDs, Mura classification system
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    • At present, the domestic industries of flat panel liquid crystal display have grown up rapidly, and the quality of LCDs becomes more and more important when there are a lot of LCDs around our lives. A critical factor of LCD panel quality is“Mura”. It is the un-uniform phenomenon in LCD panels. Traditionally, the quality of LCD panels is detected by human eyes, but it is subjective without any common criterion. In the recent years, an automation Mura inspection system has been developed by TTLA (Taiwan TFT LCD Association), which can calculate the attributes of Mura defects quickly to make the inspection process efficient and to make the judgment consistently.

    In addition, evaluating the ranks of Mura is always subjective, and serious disagreements and controversy may arise between LCD manufacturers and customers. There is lacking of Mura classification system in the present automation Mura inspection system. Although the serious degree of Mura defects was presented by JND values (Mura quality criterion), multiple JNDs in this vision model were defined as the comparison ratio of the Mura contrast (C) to the “one contrast threshold” according to SEMI (2002). However, some literatures reporting a non-linear relationship between contrast and multiple JNDs in human visual performance, so it is not uniformly to apply JND values in this vision model to establish the Mura rank standards from 1 to 3, 3 to 5……etc. Therefore, the experiment was designed in this research to obtain fitting functions of multiple JNDs for six typical Mura types.

    From the experimental result, non-linear functions were obtained, and then, the transformed function was found to modify original vision model. Finally, Mura ranking standard and Mura classification system were developed to be a standard communication platform for customers and suppliers.

    摘要 i Abstract ii 誌謝 iv Table of Contents v List of Figures viii List of Tables x Chapter1 Introduction 1 1.1 Background 1 1.2 Motivation 2 1.3 Objectives 3 1.4 Research framework 4 Chapter2 Literature Review 6 2.1 Mura defects 6 2.1.1 The structure and the process of a TFT-LCD 6 2.1.2 The definition and the cause of Mura 9 2.2 The methods for evaluating Mura 11 2.2.1 Mura defects classes of VESA 11 2.2.2 Mura defects evaluation of LCD manufactures 13 2.2.3 The Chinese unified taxonomy for Mura of TTLA 14 2.3 Video Quality Assessment Method (DSCQS method) 16 2.4 Human visual performance 18 2.4.1 Luminance Contrast 18 2.4.2 Polarity 19 2.4.3 Visual masking and human contrast discrimination 20 2.5 Measurement of threshold in psychometrics 22 2.5.1 Classical psychophysical methods 22 2.5.2 Quest: A Bayesian adaptive psychometric method 25 Chapter 3 Methodology 28 3.1 Framework of Research Methodology 29 3.2 Experimental design 31 3.3 Subjects 32 3.4 Experimental environment and apparatus 33 3.4.1 Experimental environment 33 3.4.2 Apparatus 33 3.5 Task and procedure 34 3.6 Data collection and analysis 36 Chapter 4 Results and Discussion 38 4.1 The experimental result of multiple JNDs 38 4.1.1 The modified definition of multiple JNDs 38 4.1.2 Six Mura types’ fitting function from the Experiment 40 4.2 The result of the Mura classification system 48 4.2.1 The non-linear transformed function 48 4.2.2 Development of Mura ranking standard and Mura classification system 50 4.3 Discussion 51 4.3.1 Human visual performance and Mura Quality Criterion 51 4.3.2 The comparison of human visual sensitivity among six Mura types 52 4.3.3 Mura classification system 53 Chapter 5 Conclusions 54 References 56 Appendix 58

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