本文關鍵詞： 液晶顯示器 各向異性的導電薄膜 線陣相機 自動調焦算法　出處：《電子科技大學》2016年碩士論文　論文類型：學位論文

【摘要】：液晶顯示器(LCD)作為近現(xiàn)代崛起并流行的顯示器,在各個領域都被廣泛使用。21世紀以后,晶玻接裝技術(COG)可以讓液晶屏變得更輕量化和薄型化。而在COG技術中,各向異性的導電薄膜(ACF)則是最重要的材料之一,ACF壓合的導電通道是否良好,直接關系液晶顯示屏的質量是否良好。在國外,雖然已經有部分國家或地區(qū)研制出了ACF粒子自動檢測機,但是成本太高,檢測速度也一般。而在國內,大多數(shù)廠家還是使用傳統(tǒng)的檢測方法,通過人工使用金相顯微鏡觀察,不僅效率低,而且需要大量的人工。于是,研制出擁有獨立自主知識產權的ACF粒子自動檢測機則有著重大的意義,而作為ACF粒子自動檢測機中的基礎和核心構成之一,圖像采集系統(tǒng)的研制更顯得迫在眉睫。本文主要分析并設計了ACF粒子自動檢測中的圖像采集系統(tǒng)的硬件構成、軟件系統(tǒng)整體架構以及模塊化設計,并對系統(tǒng)各功能模塊進行了測試,主要內容如下:1.首先介紹了系統(tǒng)硬件結構的運動流程,然后設計了系統(tǒng)的軟件框架。軟件框架采用“4+1”視圖法來架構,同時按照各系統(tǒng)功能進行分模塊實現(xiàn);2.設計采集圖像模塊,主要有線陣相機及其配件(鏡頭、采集卡、光源)等的選取、PC與PLC的串口通信指令的制定、以及線陣相機自動調焦的研究;3.設計圖像處理與顯示模塊,先簡單介紹了數(shù)字圖像的一些相關的編程技術,然后研究了自動調焦算法,最后分析了圖像BMP格式的顯示方案,其中細節(jié)顯示算法解決了超大圖像顯示緩慢卡頓的問題;4.本文重點研究并設計了線陣相機的自動調焦算法。在綜合分析了常用的圖像清晰度評價函數(shù)后,根據(jù)調焦圖像中邊緣細節(jié)比較多的特點,決定采用絕對方差函數(shù)作為粗調函數(shù),Brenner函數(shù)作為精調函數(shù)的方法。這種方法既可以保證精度,又能保證整體計算速度達到要求。本文創(chuàng)新性地在ACF粒子自動檢測中使用線陣相機的自動調焦算法。在自動調焦時,本文設計的在改變物距時只采集一張圖像的方法,很好地優(yōu)化了自動調焦的速度,據(jù)我們查閱國內外重要數(shù)據(jù)庫的結果,在國內還未見相關報道。本系統(tǒng)的檢測速度不僅達到了國際平均水平,其成本還大大降低,更適用于大批量生產和普及,擁有極強的市場競爭力。
[Abstract]:Liquid crystal display (LCD) as a modern and popular display, has been widely used in all fields after the 21st century. Glass bonding technology can make the liquid crystal screen lighter and thinner. In COG technology, anisotropic conductive thin film is one of the most important materials. Whether the conductive channel of ACF is good or not is directly related to the quality of LCD. In foreign countries or regions, although some countries or regions have developed ACF particle automatic detection machine, but the cost is too high. Detection speed is also general. In China, most manufacturers still use the traditional detection method, through the manual use of metallographic microscope observation, not only low efficiency, but also need a large number of manual. It is of great significance to develop an automatic ACF particle detector with independent intellectual property rights, and as one of the basic and core components of ACF particle automatic detection machine. The development of image acquisition system is more urgent. This paper mainly analyzes and designs the hardware structure, software architecture and modular design of image acquisition system in ACF particle automatic detection. The main contents are as follows: 1. Firstly, the movement flow of the hardware structure of the system is introduced. Then the software framework of the system is designed. The software framework is constructed by "41" view method, and is implemented by modules according to the functions of each system. 2. Design the image acquisition module, select the serial communication instruction between PC and PLC, and study the automatic focusing of linear array camera. 3. The image processing and display module is designed. Firstly, some related programming techniques of digital image are introduced briefly, then the auto-focusing algorithm is studied. Finally, the display scheme of image BMP format is analyzed. The detail display algorithm solves the problem of slow display of large image. 4. This paper focuses on the research and design of the automatic focusing algorithm of linear camera. After analyzing the commonly used image definition evaluation function, according to the characteristics of more edge details in the focusing image. The method of using absolute variance function as coarse tuning function and Brenner function as fine tuning function can guarantee accuracy. This paper innovatively uses the automatic focusing algorithm of linear camera in ACF particle automatic detection. The method designed in this paper is to collect only one image when changing the object distance, which optimizes the speed of auto-focusing, according to the results of our reference to the important databases at home and abroad. The detection speed of the system has not only reached the international average level, but also its cost has been greatly reduced, which is more suitable for mass production and popularization, and has a strong market competitiveness.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41

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