包装与食品机械2025，Vol.43Issue(6)：19-29,11.DOI:10.3969/j.issn.1005-1295.2025.06.003
基于改进YOLOv5s的试管标签识别方法研究
Study on test tube label recognition method based on improved YOLOv5s
摘要
Abstract
To address the challenges in test tube label recognition,such as multiple densely-arranged fields,environmental background noise,and specular reflections,a visual detection method based on an improved YOLOv5s model is proposed.OpenCV and an optimized CLAHE function were utilized to preprocess image quality.A pre-attention layer based on field perception and multi-scale enhancement(FA-SimAM)was incorporated.The Res2Conv-RFEM hybrid module was used to replace parts of the C3 modules,thereby enhancing fine-grained perception at the character level and the ability to process dense information,while also strengthening the intrinsic relationships between fields.An optimized CBAM attention mechanism was introduced to increase focus on field features.The original CIoU loss function was replaced with the FA-NWD loss function,improving the detection performance for extremely small targets and enhancing dynamic adaptation capability for fields.The results show that the improved model achieved an mAP of 87.3%,a recall of 87.5%,and a precision of 89.2%,representing improvements of 12.3,7.2,and 7.1 percentage points,respectively,compared to the original YOLOv5s model.This research provides support for related fields in medical identification.关键词
试管标签/YOLOv5s/FA-SimAM/混合模块/CBAM优化Key words
test tube label/YOLOv5s/FA-SimAM/hybrid module/optimized CBAM分类
轻工纺织引用本文复制引用
金诚,芦金石,季旭,冯怡然..基于改进YOLOv5s的试管标签识别方法研究[J].包装与食品机械,2025,43(6):19-29,11.基金项目
国家重点研发计划项目(2018YFD0400800) （2018YFD0400800）
辽宁省教育厅科研项目(JYTMS20230395) （JYTMS20230395）
