多特征矩融合的液晶屏字符缺陷检测算法  

LCD character defect detection algorithm based on multi-feature moment fusion

作　　者：陈昕 方成刚[1] CHEN Xin;FANG Cheng-gang(School of Mechanical and Power Engineering,Nanjing University of Technology,Nanjing 211800,China)

机构地区：[1]南京工业大学机械与动力工程学院,江苏南京211800

出　　处：《液晶与显示》2022年第10期1326-1333,共8页Chinese Journal of Liquid Crystals and Displays

摘　　要：为了实现液晶屏字符高效、精准的自动化检测,针对液晶屏字符显示的断线、亮度缺陷,提出一种基于多特征矩融合的液晶屏字符缺陷检测算法。首先提取原始液晶屏图像中ROI区域,使用Hu不变矩来描述字符的结构特征,采用Zernike矩来弥补Hu矩所不能描述的高阶矩信息;然后使用颜色矩来描述字符的颜色特征,采用灰度矩弥补颜色矩所不能描述的灰度信息,并运用2DPCA技术融合上述矩阵,通过欧氏距离来衡量标准图像融合特征矩阵与待检测图像融合特征矩阵之间的相似度,通过设定相似度阈值来达到缺陷检测的目的。实验的客观和主观评价结果表明:主观上,该算法具有一定的稳定性、实用性;客观上,该算法相比于同类算法具有较低的误判率1%、漏判率0%以及较高的效率0.6 s,基本满足实际检测需求。In order to realize the automatic detection of LCD characters efficiently and accurately,a character defect detection algorithm based on multi-feature moment fusion was proposed for the disconnection and brightness defects of LCD character display.Firstly,the ROI region of the original LCD image was extracted,Hu invariant moments were used to describe the structural characteristics of characters,and Zernike moments were used to compensate for the information of higher moments that Hu moments could not describe.The color moment was used to describe color features of the characters,and the gray moment was used to make up the gray information that the color moment can not describe.The matrices were fused using 2DPCA technology.The similarity between the standard image fusion characteristic matrix and the image fusion characteristic matrix to be detected were measured by Euclidean distance.By setting the similarity threshold,the goal of defect detection was achieved.Experiment results show that the algorithm is stable and practical subjectively.Objectively,compared with the similar algorithms,the algorithm has a lower false judgment rate of 1%,a lower misjudgment rate of 0%and a higher efficiency of 0.6 s,basically meeting the actual detection needs.

关 键 词：HU矩 ZERNIKE矩 颜色矩 灰度矩 2DPCA 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]