辽宁石油化工大学学报

辽宁石油化工大学学报 ›› 2014, Vol. 34 ›› Issue (6): 74-78.DOI: 10.3696/j.issn.1672-6952.2014.06.016

• 计算机与自动化 • 上一篇    下一篇

基于字符特征叠加提取与B P神经网络的字符识别

沈清波,常龙昆   

  1. ( 辽宁石油化工大学信息与控制工程学院, 辽宁抚顺1 1 3 0 0 1)
  • 收稿日期:2014-06-25 出版日期:2014-12-25 发布日期:2017-07-14
  • 作者简介:沈清波( 1 9 5 8 - ) , 男, 硕士, 副教授, 从事自适应控制、 嵌入技术、 系统辨识和神经网络技术的教学和研究; E - m a i l :q i n g b o s h e n@1 6 3. c o m。
  • 基金资助:
    辽宁石油化工大学大学生创新训练计划项目( 2 0 1 3 0 3 5) 。

Research on Character Recognition Based on Repeated Character Feature Extraction and BP Network

Shen Qingbo, Chang Longkun   

  1. (School of Information and Control Engineering, Liaoning Shihua University , Fushun Liaoning 113001, China)
  • Received:2014-06-25 Published:2014-12-25 Online:2017-07-14

摘要: 摘 要:  由于字符的种类繁多, 并且同一字符又有多种字体, 而传统的字符识别方法不能充分利用字符本身
的特征, 因此造成识别的字符种类单一、 识别效果不理想等问题。提出一种通过字符特征叠加提取结合B P神经网
络识别字符的方法, 从单一字符图像中提取到更多的字符特征, 利用B P神经网络自我学习的特点, 设计了字符识别
系统, 再用 VC编程完成识别过程的仿真。结果证明, 用本文提出的方法进行字符识别, 识别的字符种类多、 识别率
高、 识别时间短。

关键词:  字符识别, 叠加提取, B P神经网络, VC, 识别仿真

Abstract: There are many types of characters, and each type of character has a variety of fonts. The traditional character recognition methods can not make full use of the features of the character itself. Therefore, only one type of character can be recognized and the recognition effect is not ideal. A kind of character recognition method was presented based on repeated character feature extraction and BP neural network. The proposed method extracted more features of the character itself for a single character image, and the character recognition system by taking advantage of the BP neural network selflearning characteristic was designed. Finally, the recognition process simulation with VC programming was completed. The VC simulation showed that the proposed method could recognize many types of characters, the recognition rate was high and the recognition time was short.

Key words: haracter recognition, Repeated extraction, BP network, VC, Recognition simulation

引用本文

沈清波,常龙昆. 基于字符特征叠加提取与B P神经网络的字符识别[J]. 辽宁石油化工大学学报, 2014, 34(6): 74-78.

Shen Qingbo, Chang Longkun. Research on Character Recognition Based on Repeated Character Feature Extraction and BP Network[J]. Journal of Liaoning Petrochemical University, 2014, 34(6): 74-78.

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链接本文: http://journal.lnpu.edu.cn/CN/10.3696/j.issn.1672-6952.2014.06.016

               http://journal.lnpu.edu.cn/CN/Y2014/V34/I6/74