手写体汉字笔划提取方法。
本文提出一种识别在线手写汉字笔划的模糊属性自动机，为汉字识别打下了基础。
A fuzzy attributed automaton for on-Iine recognition of Chinese character strokes is proposed.
给出了十码汉字编码法的识别码提取算法。在对汉字笔划分解的基础上，根据运用的字符特征给出了识别码的提取算法。
On the basis of resolving to Chinese character stroke, this thesis presents the abstraction algorithm which recognition code used according to the character characteristic.
手书“北京2008”借汉字形态之神韵，将中国人对奥林匹克的千万种表达浓缩于简洁的笔划中。
The words "Beijing 2008" also resemble the vivid shapes of Chinese characters in handwriting, voicing in concise strokes of the countless feelings Chinese people possess towards the Olympics.
该算法可对书写工整的汉字进行有效笔划提取。
This algorithm can extract handwritten Chinese characters stroke for formal Chinese characters.
一些汉字将会增加一些笔划，因此会和以前的繁体字更加相像。
Some characters will have more strokes added and thus be brought closer to their earlier, more complicated forms.
查询你想学的汉字，你马上可以学到这个汉字的结构，部首，书写笔划，组词，解释，例句，还能校正发音。
Look up the character you want to learn, then you will learn the character's structure, radical, demo, phrase, explanation, example and pronunciation at the same time.
提出以计算象素点的方向游程长度为基础，完全基于汉字的结构知识的笔划提取算法。
Put forward the calculation that pixel direction distance length as foundation, the stroke extraction way according to the structure knowledge of Chinese characters completely.
根据笔划编码字典和笔划统计信息，设计了笔划编码汉字输入的方法和实现该方法的键盘。
On the basis of the coding dictionary and statistical data, we have devised a keyboard input method and designed a kind of key arrangement for the method.
提出一个基于多重曲率计算的角点检测算法，对联机手写汉字识别中的笔划拐点进行提取。
An algorithm for stroke corner detection based on curvature multi-calculation is proposed to extract characteristics for OLCCR (on-line handwritten Chinese character recognition).
在实现结构分析法识别手写汉字时，笔划抽取是关键所在。
In developing handprinted Chinese characters recognition system by the structural approach. the stroke extraction is all important problem.
在实现结构分析法识别多字体印刷汉字时，笔划抽取是关键所在。
In developing the multi-fonts Chinese character recognition system by structural approach, the stroke extraction is an important problem.
以笔划为基元结合笔划的顺序来表示汉字的结构信息，在此基础上提出了一种手写汉字识别的匹配算法。
This paper takes stroke segment as pattern primitive to represent the structure information of Chinese character. On the basis, a new algorithm to recognize handwritten Chinese character is proposed.
在特征提取方面，给出了汉字结构点，连通体，封闭区域，笔划等特征的提取方法。
Proposed feature extraction methods for structure, connected body, closed area and stroke in Chinese character's feature extraction.
本文提出了从汉字点阵中直接抽取笔划特征的新算法，省去了细化过程。
An algorithm for stroke segment extraction directly from Chinese character dot matrix is presented. It avoids the process of thining.
对于汉字的规则笔划和不规则笔划，分别采用了不同的变倍方法，并且采取了一系列措施以保证变倍后的文字质量。
Different scaling methods are adopted for both regular strokes and irregular strokes of Chinese characters and steps are taken to guarantee the quality during scaling.
手写汉字中笔划、部件及其位置关系均产生较大变化，这种变化是引起手写汉字特征不稳定的主要因素。
The strokes, components and their position are changed in handwritten Chinese characters, which is the main reason of what makes the features of handwritten Chinese characters unstable.
手写汉字中笔划、部件及其位置关系均产生较大变化，这种变化是引起手写汉字特征不稳定的主要因素。
The strokes, components and their position are changed in handwritten Chinese characters, which is the main reason of what makes the features of handwritten Chinese characters unstable.
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