基于BP神经网络的维吾尔联机手写字符识别  

On-line & Handwritten Uyghur Character Recognition Based on BP Neural Network

作　　者：任宏宇[1] 袁保社[1] 田园[1] 

机构地区：[1]新疆大学信息科学与工程学院,新疆乌鲁木齐830046

出　　处：《微电子学与计算机》2010年第8期238-241,共4页Microelectronics & Computer

摘　　要：维吾尔文字的书写特点,给手写字符识别带来了很大的技术难题.提出了利用BP神经网络进行手写维吾尔文字符识别的方法.根据手写体运动轨迹进行特征提取,得到14维的特征编码,利用此编码对BP神经网络进行训练和学习,形成良好的识别系统.实验表明,该方法提高了字符识别的准确率.The written characteristic of Uyghur language has brought difficult broblems for handwritten character recognition in technology. This paper proposes a method of handwriting recognition of Urghur letters using BP neural network. According to the tracks of the script, the method extracts features of the letters, forms a coding with fourteen dimensions. Secondly, trains the BP neural network and studies using the coding, builds good system of recognition. Simulations show that this method enhanced the veracity of recognition.

关 键 词：维吾尔文 神经网络 手写字符识别 特征提取 

分 类 号：TP391.43[自动化与计算机技术—计算机应用技术]