基于神经网络的字符识别技术研究

Study on ANN Based Character Recognition

本文在分析人工神经网络理论和图象处理及其特征提取理论的基础上，探讨了网络结构、特征编码、算法的实现、学习样本的收集、网络参数的选择及ＢＰ算法缺陷等问题，设计并实现了一种基于神经网络的字符识别系统。并针对ＢＰ算法的缺陷问题提出改进方法并得以实现，提出建立奇异样本特征库的方法使学习的效率大大的提高。实践证明采用改进型ＢＰ算法的三层前向无反馈神经网络进行手写字符识别是完全可行和实用的。

The theory of Artificial Neural Networks and image processing are analyzed. ANN theory is also investigated . A Back Propagation network is used for classification. Based on the ANN and feature extraction, a character recognition and entry system is developed. Its drawbacks are discussed. Some solutions are presented. An odd feature database is constructed to promote the performance for learning. A 3 layer feedforward network has been proved that it has the ability to identify hand written characters.