东南大学学报（英文版）Issue(1)：27-31,5.DOI:10.3969/j.issn.1003-7985.2014.01.006
基于小波变换和梯度方向的脱机手写藏文字符特征提取方法
Wavelet transform and gradient direction based feature extraction method for off-line handwritten Tibetan letter recognition
摘要
Abstract
To improve the recognition accuracy of off-line handwritten Tibetan characters the local gradient direction histograms based on the wavelet transform are proposed as the recognition features.First for a Tibetan character sample image the first level approximation component of the Haar wavelet transform is calculated.Secondly the approximation component is partitioned into several equal-sized zones. Finally the gradient direction histograms of each zone are calculated and the local direction histograms of the approximation component are considered as the features of the character sample image.The proposed method is tested on the recently developed off-line Tibetan handwritten character sample database.The experimental results demonstrate the effectiveness and efficiency of the proposed feature extraction method.Furthermore compared with the detail components the approximation component contributes more to the recognition accuracy.关键词
模式识别/小波变换/梯度方向/藏文/手写字符Key words
pattern recognition/wavelet transform/gradient direction/Tibetan/handwritten character分类
信息技术与安全科学引用本文复制引用
黄鹤鸣,达飞鹏,韩晓旭..基于小波变换和梯度方向的脱机手写藏文字符特征提取方法[J].东南大学学报（英文版）,2014,(1):27-31,5.基金项目
The National Natural Science Foundation of China No．60963016 the National Social Science Foundation of China No．17BXW037． （）
