2012,48(26)
1 引言
OLED(Organic Light Emitting Display),即有
机电致发光显示器,作为当今显示界的新宠而迅速
崛起。因其具有低功耗、宽视角、主动发光、易于实
现柔性制造等优点
[1]
受到了人们越来越多的关注。
复杂的工艺使得产品不可避免地会出现微小的缺
陷,这些细小的缺陷对 OLED 的显示效果造成影响,
为了提高产品的显示质量和成品率,必须在OLED 的
制造中增加一个缺陷检测环节。统计显示,造成这
种缺陷有电气因素也有非电气因素,例如,工艺过程
中微小颗粒的污染;ITO 电极的失效,信号电极、扫描
电极的短路和断路;驱动 IC 与屏上有源器件连接不
面向 OLED 屏像素缺陷检测的新方法
汪志亮
1
,高 健
1
,赵伟明
2
WANG Zhiliang
1
, GAO Jian
1
, ZHAO Weiming
2
1.广东工业大学 机电工程学院,广州 510006
2.东莞宏威数码机械有限公司,广东 东莞 523656
1.School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510006, China
2.Dongguan Anwell Technologies Limited, Dongguan, Guangdong 523656, China
WANG Zhiliang, GAO Jian, ZHAO Weiming. New method for OLED pixel defect detection. Computer Engi-
neering and Applications, 2012, 48(26):177-180.
Abstract:Organic LED(OLED)screen often exists defects which have the characteristics of small size, low con-
trast, indifferent gray value. These defects will cause detection problem. Traditional thresholding method cannot de-
tect the defects effectively. This paper proposes a multi-image-subtraction method to detect pixel defects of OLED
screen. Based on the initial process of median filtering and image enhancement, the image is processed with pixel
template extracting and subtraction operation, until a better contrast image is achieved. A K-means clustering meth-
od is selected to segment the image and detect the defects from the processed image. Through the tools of Labview
and IMAQ Vision software package, this method proposed in the paper is implemented and verified by an OLED im-
age. The test result shows that this method can detect defects effectively and the smallest defects can be 8 µm×8 µm.
Key words:image processing; Organic Light Emitting Display(OLED); defect detection; subtracting method;
K-means clustering
摘 要:有机发光显示器OLED(Organic LED)的内部像素缺陷常由于尺寸小、对比度不高、且灰度与像素轮廓灰
度相近等问题,在使用传统阈值分割方法处理时会将像素轮廓保留下来,因而不能达到缺陷的有效检测目的。提出
一种多次迭代差影法的OLED屏像素缺陷检测方法。该检测算法在对图像进行中值滤波和图像增强处理后,对图像
实施多次像素模板提取和差影运算,获取到对比度较低的缺陷图,运用K-均值聚类方法对图像进行分割,从而较好地
实现缺陷的识别。运用Labview和IMAQ Vision 软件包工具,编程实现所提出的算法,并通过实际获取的OLED
图片验证了方法的有效性。结果表明,该方法能很好地保持缺陷的细节,并能检测到8 µm×8 µm的微小缺陷。
关键词:图像处理;有机发光显示器(OLED);缺陷检测;差影法;K-均值聚类
文章编号:1002-8331(2012)26-0177-04 文献标识码:A 中图分类号:TP393
基金项目:广东省科技计划粤港关键领域重点突破项目(No.2009A091300001);广东省中国科学院全面战略合作(No.2009B091300057)。
作者简介:汪志亮(1985—),男,硕士研究生,主要研究方向为 OLED 显示屏缺陷检测;高健(1962—),女,博士生导师,主要研究
方向为曲面修复、反求工程、缺陷检测等。
收稿日期:2011-03-09 修回日期:2011-05-30 CNKI 出版日期:2011-08-04
DOI:10.3778/j.issn.1002-8331.2012.26.039 http://www.cnki.net/kcms/detail/11.2127.TP.20110804.1609.125.html
Computer Engineering and Applications 计算机工程与应用
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