包装与食品机械2025，Vol.43Issue(3)：80-87,8.DOI:10.3969/j.issn.1005-1295.2025.03.009
基于注意力机制的印刷包装标签文本自动定位检测方法
Attention mechanism-based automatic localization and detection method for text in printed packaging labels
摘要
Abstract
To address the challenges of multilingual texts,dense arrangements,and extreme aspect ratios in printed labels,this study proposes an attention mechanism-based localization method for text regions in printed packaging labels.The conventional convolution in ResNet's Bottleneck was replaced with dilated convolution featuring learnable spacing to expand the network's receptive field.Global and local attention mechanism modules were incorporated to enhance feature extraction capabilities for textual information in the backbone network.A residual attention mechanism module was added to the feature pyramid network to guide adaptive fusion of multi-scale features.Ablation experiments showed that compared to DBNet,the proposed model improved F1-scores by 1.2,2.1,and 1.7 percentage points respectively.Comparative tests on ICDAR2015,Total-Text,and a self-built dataset demonstrated superior detection performance over mainstream text detection models(EAST,PSENet,FCENet,DPText-DETR,DBNet),achieving F1-scores of 88.3%,86.1%,and 85.1%.This research provides assurance for intelligent online inspection of printed labels.关键词
标签检测/文本定位/注意力机制/可学习间距扩张卷积Key words
label detection/text localization/attention mechanism/dilated convolution with learnable spacing分类
通用工业技术引用本文复制引用
张鹏涛,李文峰,宋强..基于注意力机制的印刷包装标签文本自动定位检测方法[J].包装与食品机械,2025,43(3):80-87,8.基金项目
新疆维吾尔自治区自然科学基金面上项目(2021D01A203) （2021D01A203）
