佛山科学技术学院学报（自然科学版）2024，Vol.42Issue(3)：1-13,13.
基于增强多层次特征融合的自然场景文本检测
Natural scene text detection based on enhanced multi-level feature fusion
摘要
Abstract
Aiming at the detection problems caused by unfocused small text,complex background text and wide-spaced curved text in natural scene images,a natural scene text detection method based on enhanced multi-level feature fusion was proposed.It includes the Local Attention Feature Enhanced(LAFE)module and the Multi-level Enhanced Feature Fused(MEFF)module.LAFE module expands the sensory field of the network by stacking dilated convolution and enhances the classification ability of pixels by combining channels and spatial attention.MEFF module,as a multi-level enhanced feature connection branch,introduces deformable convolution to enhance the information fusion between feature graphs.Experimental results show that the proposed method has good performance on common text data sets.Among them,the comprehensive index F of ICDAR2015 and Total-Text data sets reached 88.1%and 86.5%,respectively,which increased by 0.8%and 1.8%compared with the original method.关键词
自然场景文本检测/注意力机制/像素点分类/空洞卷积/特征融合Key words
natural scene text detection/attention mechanism/pixel point classification/dilated convolution/feature fusion分类
信息技术与安全科学引用本文复制引用
周燕,韦勤彬,廖俊玮,曾凡智,刘翔宇,周月霞..基于增强多层次特征融合的自然场景文本检测[J].佛山科学技术学院学报（自然科学版）,2024,42(3):1-13,13.基金项目
国家自然科学基金资助项目(61972091) （61972091）
广东省自然科学基金资助项目(2022A1515010101,,2021A1515012639) （2022A1515010101,,2021A1515012639）
