[1]蔡晓娟,黄鹤鸣. 基于多投影的脱机手写藏文字符特征提取方法[J].计算机技术与发展,2016,26(03):93-96.
　CAI Xiao-juan,HUANG He-ming. Feature Extraction Method of Off-line Handwritten Tibetan Character Based on Multiple Projection[J].,2016,26(03):93-96.
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 基于多投影的脱机手写藏文字符特征提取方法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年03期
页码:
93-96
栏目:
智能、算法、系统工程
出版日期:
2016-03-10

文章信息/Info

Title:
 Feature Extraction Method of Off-line Handwritten Tibetan Character Based on Multiple Projection
文章编号:
1673-629X（2016)03-0093-04
作者:
 蔡晓娟; 黄鹤鸣
 青海师范大学 计算机学院
Author(s):
 CAI Xiao-juan; HUANG He-ming
关键词:
 ; 脱机手写藏文字符; 特征提取; 投影向量; 归一化; 多投影归一化向量
Keywords:
 ; off-line handwritten Tibetan character; feature extraction; projection vector; normalization; multiple projection normalized vector
分类号:
TP301
文献标志码:
A
摘要:
 脱机手写藏文字符的识别能够促进藏文化的发展和传播，其识别的方法是根据脱机手写藏文字符图像的特征进行识别。由于原始定义下的行列投影向量对于脱机手写藏文字符图像的表示不够充分，文中提出一种基于多投影归一化的脱机手写藏文字符特征提取算法。首先，对脱机手写藏文字符图像分别在横向、纵向、主对角线方向和次对角线方向进行投影，得到行投影向量、列投影向量、主投影向量和次投影向量；然后，对投影向量进行归一化处理，将归一后的向量合并成一个向量，即为该脱机手写藏文字符图像的特征向量；最后，使用KNN分类器对测试样本进行识别。对建立的脱机手写藏文字符样本数据库中的样本进行实验。结果表明，该算法不仅计算简单，而且有较好的识别效果。
Abstract:
 Off-line handwritten Tibetan character recognition can promote the development and propagation of Tibetan culture,and the method of classification is based on the feature of off-line handwritten Tibetan character image. Since original definition of projection en-tropy does not make full use of image information,a feature extraction method of off-line handwritten Tibetan character based on multiple projection normalization is proposed. Firstly,an off-line handwritten Tibetan character image is scanned in horizontal,vertical,main diag-onal and secondary diagonal directions to create a row projection vector,a column projection vector,a main projection vector and a sec-ondary projection vector. Secondly,all projection vectors are normalized to create a multiple projection normalized vector that is the fea-ture vector for this character image. Finally,KNN classifier is used in classification. The proposed method is tested on the developed off-line Tibetan handwritten character sample database. The experimental results demonstrate that the proposed method is not only easy in cal-culation but also efficient in recognition accuracy.

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更新日期/Last Update: 2016-06-12