Offline recognition of Chinese handwriting by multifeature and multilevel classification
Offline recognition of Chinese handwriting by multifeature and multilevel classification
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DOI：
10.1109/34.682186
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发表时间：
1998-05-01
影响因子：
23.6
通讯作者：
Shyu, IS
中科院分区：
文献类型：
--
作者：
Tang, YY;Tu, LT;Shyu, IS
其中最具挑战性的课题之一是手写体识别，尤其是脱机手写体识别。本文提出了一种基于多特征多级分类的手写体汉字软线识别系统。该系统使用了10类多特征，如边缘形状特征、笔划密度特征和笔划方向特征。多级分类方案由一个组分类器和一个五级特征分类器组成，其中开发了两项新技术：重叠聚类和高斯分布选择器。对5，401个日常使用的汉字进行了识别实验。对于独特的候选人，识别率约为90%。而10个候选人的多项选择题则为98%。
One of the most challenging topics is the recognition of Chinese handwriting, especially off line recognition. In this paper, an oft line recognition system based on multifeature and multilevel classification is presented for handwritten Chinese characters. Ten classes of multifeatures, such as peripheral shape features, stroke density features, and stroke direction features, are used in this system. The multilevel classification scheme consists of a group classifier and a five-level character classifier, where two new technologies, overlap clustering and Gaussian distribution selector, are developed. Experiments have been conducted to recognize 5,401 daily-used Chinese characters. The recognition rate is about 90 percent for a unique candidate. and 98 percent for multichoice with 10 candidates.