青岛大学学报（自然科学版）2025，Vol.38Issue(3)：35-41,7.DOI:10.3969/j.issn.1006-1037.2025.03.06
基于文字结构的自切分手写汉字文本识别方法
Self-segmentation Recognition Method for Handwritten Chinese Character Text Based on Character Structure
摘要
Abstract
Handwritten Chinese text has complex structures,diverse writing styles,and unclear character boundaries,making traditional segmentation-free recognition methods prone to misalignment and recognition errors.A handwritten Chinese text recognition method based on a segmentation-based recognition framework was proposed,and a Swin attention mechanism module with self-attention and a sliding window approach was inte-grated,along with the embedding of the self-information of radicals.Experimental results show that the accuracy of the proposed method achieves 94.07%for handwritten Chinese text recognition,outperforming the current common recognition SVTR method by a mar-gin of 0.57%.关键词
手写汉字文本识别/注意力机制/部首自信息/卷积神经网络Key words
handwritten Chinese text recognition/attention mechanism/self-information of radicals/convolutional neural network分类
信息技术与安全科学引用本文复制引用
顾一漫,张小垒..基于文字结构的自切分手写汉字文本识别方法[J].青岛大学学报（自然科学版）,2025,38(3):35-41,7.基金项目
国家自然科学基金(批准号:62373205,62033007)资助 （批准号:62373205,62033007）
山东省泰山学者项目(批准号:tstp20230624)资助 （批准号:tstp20230624）
青岛大学系统科学联合研究项目(批准号:XT2024101)资助. （批准号:XT2024101）
