福建电脑2026，Vol.42Issue(3)：17-22,6.DOI:10.16707/j.cnki.fjpc.2026.03.004
融合多尺度CNN和结构特征的傣文字符识别
Tai Lue Character Recognition by Integrating Multi-scale CNN and Structural Feature Fusion
顾亚楠 1周文1
作者信息
- 1. 贵州机电职业技术学院信息工程系 贵州 都匀 558000
- 折叠
摘要
Abstract
As an ethnic script with a long history,the Dai language features complex character structures and high glyph similarity,making it difficult for single-feature methods to fully capture character details.To address this,this paper proposes a Dai character recognition model that integrates multi-scale CNN and structural features.First,structural attributes such as HOG feature vectors and projection histograms are extracted from character images to preserve more detailed information.Then,a multi-scale convolutional module is used to extract deep features at different levels.The structural and deep features are fused,and a global average pooling(GAP)layer is introduced at the end of the network to replace traditional fully connected layers for classification.This simplifies the computational process while significantly reducing the number of parameters.Experimental results show that the model achieves a recognition accuracy of 98.71%,outperforming other methods and yielding the best recognition performance.关键词
傣文字符识别/多尺度卷积神经网络/结构特征/特征融合Key words
Dai Character Recognition/Multi-scale CNN/Structural Features/Feature Fusion分类
信息技术与安全科学引用本文复制引用
顾亚楠,周文..融合多尺度CNN和结构特征的傣文字符识别[J].福建电脑,2026,42(3):17-22,6.
