液晶与显示2025，Vol.40Issue(3)：439-447,9.DOI:10.37188/CJLCD.2024-0295
基于改进YOLOv8n的液晶屏Mura缺陷检测
Mura defect detection of LCD screen based on improved YOLOv8n
摘要
Abstract
To address the problem of insufficient accuracy in LCD Mura defect detection due to low contrast and diverse scale differences,from the perspective of improving the model's performance in detecting small-scale defects and weak defects,an improved YOLOv8n-based LCD Mura defect detection model,YOLO-D3MNet,is proposed.Firstly,the backbone and neck networks of the model are reconstructed through the introduction of the ConvNeXtv2 module,which improves the weak feature extraction capability of the model under the background of complex texture.Secondly,for the problem of insufficient cross-channel communication of feature information in the detection head module,an efficient decoupling head combining the channel shuffle strategy and depth-separable convolution is proposed to promote the information flow between different feature channels and reduce the model computation power requirement.Finally,to address the problem that the intersection and concatenation ratio metric based on prediction box and truth box is sensitive to the positional bias of small-scale defects,the normalized Gaussian Wasserstein distance loss function is introduced to provide more positive sample candidate boxes,which improves the model's detection performance of Mura defects.The precision,recall and mAP50 of the improved YOLO-D3MNet model are 92.9%,88.8%and 94.8%,respectively.Compared to the base model YOLOv8n,the precision,recall and mAP50 of the YOLO-D3MNet model are improved by 3.4%,2.7%and 3.6%,respectively,while the GFLOPs of the model are reduced by 24.7%.Compared with mainstream target detection models such as YOLOv5n,the experimental results show that the YOLO-D3MNet model proposed in this paper has better performance in LCD Mura defect detection.关键词
Mura缺陷/液晶屏/目标检测/深度学习/微弱特征Key words
Mura defects/LCD screen/object detection/deep learning/weak feature分类
计算机与自动化引用本文复制引用
陈顺龙,廖映华,林峰,舒成业..基于改进YOLOv8n的液晶屏Mura缺陷检测[J].液晶与显示,2025,40(3):439-447,9.基金项目
宜宾三江新区"揭榜挂帅"科技项目(No.2022JBGS001) （No.2022JBGS001）
宜宾市引进高层次人才项目(No.2022YG01) （No.2022YG01）
四川省中央引导地方科技发展专项(No.2024ZYD0300) Supported by Yibin Sanjiang New Area Unveiling Hanging Project(No.2022JBGS001) （No.2024ZYD0300）
Yibin High-Level Talents Introduction Plan(No.2022YG01) （No.2022YG01）
Special Project for Guiding Local Science and Technology Development by Central Government of Sichuan Province(No.2024ZYD0300) （No.2024ZYD0300）
