印刷体汉字特征点是印刷体汉字分类的重要特征之一。
Print Chinese character feature point is one of the important features for print Chinese character classification.
本文描述了采用这种网络模型实现的印刷体汉字识别系统。
The paper describes a printed Chinese character recognition system by such network.
本文提出了一种基于人工神经网络解决手写印刷体汉字识别的方法。
A handprinted Chinese character recognition method based on artificial neural network is presented in this paper.
本文介绍用于识别手写印刷体汉字的二维扩展属性文法方法中文法归约阶段的工作。
The work on grammar reductions in Two-Dimensional Extended Attribute Grammars is presented for the recognition of hand-printed Chinese characters.
本文提出一种手写印刷体汉字识别方法，使用该方法无需先对汉字进行细化和平滑处理。
A proper method for the recognition of handprinted Chinese characters is presented here, without thinning the character image and smoothing it before hand.
用本文的方法来跟踪印刷体汉字的轮廓边缘，提取汉字轮廓的链式方向码序列，取得了令人满意的结果。
Using the method described in this paper the edges of printed Chinese Characters were tracked down to extract the sequence of their chain direction code, and the results were satisfactory.
本文从手写印刷体汉字的计算机光学输入的离散模式出发，提出一种称为s - E坐标的特征提取的新方法。
A new feature extraction method, named S-E coordinate, is proposed from the computer optical input discrete pattern of handprinted Chinese characters.
最后该文给出了印刷体和手写体汉字笔段提取的实验结果。
Experimental results for several fonts of printed Chinese characters and handwritten Chinese characters show that the proposed method is effective and robust.
最后该文给出了印刷体和手写体汉字笔段提取的实验结果。
Experimental results for several fonts of printed Chinese characters and handwritten Chinese characters show that the proposed method is effective and robust.
应用推荐