中国造纸2025，Vol.44Issue(11)：192-199,8.DOI:10.11980/j.issn.0254-508X.2025.11.026
基于机器视觉与深度学习的烟用商标纸质量评价方法研究
Study on Quality Evaluation Method of Cigarette Trademark Paper Based on Machine Vision and Deep Learning
摘要
Abstract
To investigate the application of machine vision technology integrating deep learning in evaluating the quality inspection results of cigarette trademark paper,this study proposed a comprehensive evaluation method.A high-resolution industrial camera,customized light sources,and specialized software systems were employed to construct an annotated dataset.Dynamic threshold ORB feature detection,opti-mized RANSAC registration,and multi-band fusion strategies were adopted,effectively eliminating stitching seams.The images PSNR of 38.9 dB and SSIM of 0.94.For feature recognition,the YOLOv8 model was enhanced by introducing a CBAM attention module,combined with a ResNet-34 backbone network and FPN multi-scale feature fusion,achieving 99.4%mAP50,99.6%recall,and 99.0%precision on the test set.A dual-branch Siamese network was designed to compute similarity by fusing SIFT descriptors and deep semantic features,achieving average recognition accuracies of 97.64%for small box trademark paper and 95.85%for carton trademark paper.关键词
机器视觉/深度学习/YOLOv8/商标纸质量检测/相似度计算Key words
machine vision/deep learning/YOLOv8/cigarette trademark paper quality inspection/similarity computation分类
轻工纺织引用本文复制引用
王律,陈仁宇,许彦旻,张俊,彭云发,詹映,曹昌清,斯勇,沈强,丁冉,林森,沈陟彦,薛辰,夏志骋..基于机器视觉与深度学习的烟用商标纸质量评价方法研究[J].中国造纸,2025,44(11):192-199,8.基金项目
上海烟草集团有限责任公司科技项目(K2023-1-024P). （K2023-1-024P）
