Automatic blemish detection in liquid crystal flat panel displays

计算机科学 液晶 液晶显示器 计算机图形学(图像) 光学 平板 计算机视觉 物理 操作系统
作者
William B. Pratt,Sunil S. Sawkar,Kevin O'Reilly
出处
期刊:Proceedings of SPIE 被引量:34
标识
DOI:10.1117/12.301232
摘要

Visual defects sometimes occur during the manufacturing of flat panel liquid crystal displays (LCDs). One class of defects includes a variety of blemishes variously called stain (English), mura (Japanese) or alluk (Korean). These blemishes appear as low contrast, non-uniform brightness regions, typically larger than single pixels. They are caused by a variety of factors such as non-uniformity distributed liquid crystal material and foreign particles within the panel. Such blemishes cannot be repaired. Automatic inspection systems, designed for pixel and line defect detection, have had difficulty accurately detecting and quantifying LCD blemishes. At present, most blemish detection is performed by human inspectors. This paper describes a recently developed automatic inspection system, which reliably detects, quantifies and classifies LCD blemishes in the presence of single pixel and line pixel defects that tend to obscure the subtle blemishes. The algorithm underlying this system, called MuraLookTM, uses conventional image processing operators such as convolutional filtering, morphological filtering and blob shape analysis under region-of-interest control in a novel combination to systematically separate each of over twenty different blemish patterns. Strength measures for each class of blemish are used under human operator control to grade each blemish as pass or fail. The paper discusses various types of defects in LCD panels and relates them to the MuraLook system defect class patterns. The architecture of the MuraLook defect detection system is described.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
8888发布了新的文献求助10
刚刚
刚刚
1秒前
完美世界应助拉长的绮山采纳,获得10
1秒前
高唐完成签到,获得积分10
1秒前
3秒前
Ericlibrave完成签到 ,获得积分10
3秒前
5秒前
奇数成双发布了新的文献求助10
5秒前
高唐发布了新的文献求助10
5秒前
6秒前
善学以致用应助追寻依风采纳,获得10
6秒前
annoraz完成签到,获得积分10
7秒前
丹D应助张张采纳,获得10
7秒前
丹D应助张张采纳,获得10
7秒前
倩倩发布了新的文献求助10
8秒前
毛果芸香碱完成签到 ,获得积分10
9秒前
丘比特应助勤劳哈密瓜采纳,获得10
9秒前
Frank应助fff采纳,获得10
9秒前
向阳发布了新的文献求助10
9秒前
Yini应助等待的香魔采纳,获得40
9秒前
10秒前
cymxyqf159完成签到,获得积分10
10秒前
haha发布了新的文献求助10
11秒前
WYN完成签到,获得积分20
12秒前
chenzihao完成签到,获得积分10
12秒前
actor2006完成签到,获得积分10
12秒前
12秒前
14秒前
14秒前
科研通AI6应助研友_nv2r4n采纳,获得10
15秒前
浮游应助淡然水绿采纳,获得10
15秒前
15秒前
Alina1874发布了新的文献求助10
16秒前
Jean完成签到,获得积分20
16秒前
lejunia发布了新的文献求助30
17秒前
思源应助迪迦王采纳,获得10
17秒前
18秒前
19秒前
芽芽豆完成签到 ,获得积分10
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1001
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences 500
On the application of advanced modeling tools to the SLB analysis in NuScale. Part I: TRACE/PARCS, TRACE/PANTHER and ATHLET/DYN3D 500
L-Arginine Encapsulated Mesoporous MCM-41 Nanoparticles: A Study on In Vitro Release as Well as Kinetics 500
Haematolymphoid Tumours (Part A and Part B, WHO Classification of Tumours, 5th Edition, Volume 11) 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5471950
求助须知:如何正确求助?哪些是违规求助? 4574342
关于积分的说明 14345719
捐赠科研通 4501694
什么是DOI,文献DOI怎么找? 2466457
邀请新用户注册赠送积分活动 1454550
关于科研通互助平台的介绍 1429124