基于改进YOLOv5s的大尺寸导光板缺陷检测  

Defect Detection of Large-size Light Guide Plate Based on Improved YOLOv5s

作　　者：刘霞[1] 张环宇 LIU Xia;ZHANG Huan-Yu(School of Electrical Information Engineering,Northeast Petroleum University,Daqing 163318,China)

机构地区：[1]东北石油大学电气信息工程学院,大庆163318

出　　处：《计算机系统应用》2023年第2期339-346,共8页Computer Systems & Applications

摘　　要：导光板(LGP)是液晶显示器(LCD)背光模组的主要部件.导光板的缺陷将直接影响液晶显示器的显示效果.针对导光板图像纹理背景复杂、低对比度、缺陷尺寸小等问题,本文提出了一种用于大尺寸导光板缺陷检测的AYOLOv5s网络.首先,将导光板图像进行分图处理,然后在主干部分和特征融合部分集成Transformer和注意力机制coordinate attention,并选择Meta-ACON激活函数.最后,基于自建数据集LGPDD进行了大量实验.实验结果表明,LGP缺陷检测算法的平均精度(mAP)可以达到99.20%,并且FPS可达77,可以实现在12 s/pcs内对尺寸为17英寸的导光板中的亮点、划伤、异物、磕碰伤、脏污等缺陷具有较好的实际检测效果.A light guide plate(LGP)is the main component of the backlight module of a liquid crystal display(LCD),whose defects can directly affect the display effect of LCD.To address the problems of complex texture background,low contrast,and small defect size of LGP images,this study proposes an AYOLOv5s network for defect detection of largesize LGP images.First,the LGP image is divided into different images.Then,Transformer and the attention mechanism coordinate attention are integrated in the main part and feature fusion part,and the Meta-ACON activation function is selected.Finally,massive experiments are carried out on the basis of the self-built data set LGPDD.The experimental results indicate that the defect detection algorithm for LGP enjoys the mean average accuracy(mAP)of up to 99.20%and FPS of 77,which can realize good effects in the practical detection of bright spots,scratches,foreign bodies,bumps,dirt,and other defects in the 17-inch LGP in 12 s/pcs.

关 键 词：导光板缺陷检测 分图处理 AYOLOv5s 注意力机制 深度学习 

分 类 号：TN873.93[电子电信—信息与通信工程] TP391.41[自动化与计算机技术—计算机应用技术]