基於SOPC之中小尺寸單色STN液晶模組顯示瑕疵視覺檢測系統

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研究生：	陳一龍 Yi-Long Chen
論文名稱：	基於SOPC之中小尺寸單色STN液晶模組顯示瑕疵視覺檢測系統 A Machine Vision System for Medium-Small sized Monochrome STN LCM Dot Defects Inspection Based on SOPC
指導教授：	許孟超 Mon-Chau Shie
口試委員:	阮聖彰 Shanq-Jang Ruan 鄭瑞光 Ray-Guang Cheng
學位類別：	碩士 Master
系所名稱：	電資學院 - 電子工程系 Department of Electronic and Computer Engineering
論文出版年：	2009
畢業學年度：	97
語文別：	中文
論文頁數：	89
中文關鍵詞：	機器視覺檢測、液晶顯示模組、SOPC 、DE2 、FPGA
外文關鍵詞：	Machine Vision Inspection, Liquid Crystal Display Module, SOPC, DE2, FPGA
相關次數：	點閱：295 下載：2
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上一筆

所謂的機器視覺(Machine Vision)或稱之為電腦視覺(Computer Vision)，屬於一項高度整合光學、機械與電學的應用科技。機器視覺系統已取代人眼視覺並且被廣泛的使用於諸如工業自動化、製程控制與量測自動化等，它們常被用來檢測物件以辨識其特性、異常或瑕疵等情形。典型PC-Based的機器視覺檢測系統通常包括光源照明系統、主控制電腦、取像攝影機、影像擷取卡與輸出入設備等，整套系統價格非常昂貴且開發複雜度提高。
價格與開發複雜度驅使我們建立一個低價與高速且較為彈性之解決方案，因此，本論文提出以SOPC技術為基礎之液晶模組(LCM)顯示瑕疵視覺檢測系統。我們選擇友晶科技基於Altera® Cyclone II FPGA EP2C35F672C6晶片為主，其可提供約3.5萬個LE供使用者利用且支援即時的SOPC 軟硬體協同開發環境之DE2開發平台，將視覺檢測演算程式與硬體模組實現於單顆FPGA晶片中。本視覺檢測系統實作合成後僅需9千個LE，故對於硬體資源的需求量是很低的。
最後，我們實際以100個單色液晶顯示模組進行檢測，實驗結果顯示不論是垂直斷線、水平斷線、多重斷線或隨機缺點等顯示瑕疵，均能夠在420ms時間內完全的為系統正確地檢測出來。

Machine vision (MV) also called computer vision is a highly integrated technology composed of optical, mechanical, and electrical units. Machine vision systems are increasingly used to replace human vision in a wide range of applications such as industrial automation, process control, test and measurement automation, etc. They are often used to inspect objects to determine characteristics, abnormalities or defects in the object. The typical PC-Based AOI systems are comprised generally of a lighting system, host computer, camera/frame grabber and Input/Output hardware, etc. The cost of the entire system is very expensive and complexity arises.
The complexity and cost are the major factor to encourage us to find more flexible solution with Low-cost, High-speed and rapid development solution. Therefore, A SOPC-based Machine Vision Inspection system for LCD module dot defect and the inspection methods are presented. The Terasic DE2 board is a dedicated platform that supports simultaneous HW/SW Co-Design and based on an Altera® Cyclone II FPGA chip EP2C35F672C6 , which provides about 35000 LEs for users, and is implemented as a system-on-a-programmable chip (SOPC). We only need about 9000 LEs to implement our system, so the hardward resource utilization is very low.
Finally, we use 100 pcs of LCD Module under test for our machine vision system. The experiment results indicate whether the dot defects are horizontal, vertical, hybrid, or missing dots can be correctly inspected by our system in 420ms.

目錄
論文摘要............................................................1
Abstract............................................................2
誌謝................................................................3
目錄................................................................4
圖索引..............................................................7
表索引..............................................................9
第一章 緒論..............................................10
	1.1 研究動機與目的.............................................10
	1.2 研究背景...................................................11
	1.3 全文架構...................................................11
第二章 相關知識..........................................12
	2.1 單色液晶顯示模組(Monochrome LCDM)簡介......................12
	    2.1.1 單色液晶顯示模組之結構...............................13
	    2.1.2 液晶顯示驅動IC之控制方式............................15
	    2.1.3 簡易型液晶模組顯示驅動電路...........................18
2.1.4 常見液晶顯示瑕疵及其原因探討.........................19
	2.2 機器視覺與數位影像處理.....................................20
       2.2.1 色彩空間..............................................20
          2.2.1.1 RGB色彩空間......................................21
          2.2.1.2 YUV色彩空間......................................21
		2.2.2 灰階影像.............................................21
		2.2.3 影像濾波.............................................22
2.2.4 中值濾波.............................................23
2.2.5 均值濾波.............................................24
2.2.6 影像分割(二值化).....................................25
2.2.7 閥值(臨界值)之選取方法...............................26
	2.3 自動光學檢測(AOI)系統簡介..................................28
		2.3.1典型PC Based自動光學檢測系統架構 ....................28
2.3.1.1 光源照明系統架構.............................28
2.3.1.2 CCD影像攝影機................................30
2.3.1.3影像擷取卡(Frame Grabber).....................31
2.3.1.4工業電腦(Host Computer).......................31
2.3.1.5 X-Y移動平台 .................................31
        2.3.2 自動光學檢測系統評估重點.............................32
		2.3.3 SOPC技術實現之視覺檢測系統架構.......................32
	2.4  Altera SOPC技術與Avalon Memory-Mapped簡介 .............. 33
		2.4.1 NIOS II Processor....................................34
		2.4.2 Avalon Memory-Mapped.................................35
第三章 SOPC Based視覺檢測系統硬體架構....................36
	3.1 SOPC Based視覺檢測系統簡介. ...............................36
	    3.1.1 SOPC Based視覺檢測系統開發平台.......................36
	    3.1.2 SOPC Based視覺檢測系統完整架構.......................38
	3.2 TV Decoder與VideoIN模組....................................40
        3.2.1直接記憶體存取( DMA)架構設計 .........................40
        3.2.2 TV Decoder 模組.......................................41
3.2.2.1視訊解碼晶片ADV7181控制時序..................43
3.2.2.2視訊解碼晶片ADV7181配置......................44
        3.2.3 VideoIN模組..........................................46
	3.3 DirectBIN_DMA硬體模組......................................48
	3.4 閥值參數化均值濾波器暨二值化硬體模組.......................50
	3.5 閥值參數化中值濾波器暨二值化硬體模組.......................53
	3.6 ExtractROI_DMA硬體模組.....................................57
	3.7 MeanThreshold_DMA硬體模組..................................60
3.8 串列通訊UART硬體模組...................................... 61
3.9 VGA Controller模組與影像信號輸出界面電路...................63
		3.9.1 VGA Controller硬體模組...............................63
		3.9.2 影像信號輸出界面電路 ................................66
	3.10使用SOPC Builder建立系統與整合............................67
第四章 視覺檢測系統實驗步驟與軟體演算法設計..............68
4.1視覺檢測系統實驗步驟. ......................................68
        4.1.1灰階影像擷取. ........................................70
        4.1.2 PC端之UART傳輸視窗程式. .............................71
        4.1.3影像未經濾波處理之閥值計算. ..........................72
        4.1.4影像經中值濾波處理之閥值計算. ........................74
        4.1.5影像經均值濾波處理之閥值計算. ........................75
	4.2硬體模組與PC軟體執行效能比較. .............................76
	4.3視覺檢測演算法概述. ........................................76
        4.3.1鏡頭Distortion評估. .................................77
        4.3.2視覺檢測演算法發展歷程. ..............................78
第五章 研究成果..........................................84
第六章 結論與未來展望....................................86
參考文獻.................................................87

                                

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