• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Sun, Guang-Min (Sun, Guang-Min.) (学者:孙光民) | Wang, Jing (Wang, Jing.) | Yu, Guang-Yu (Yu, Guang-Yu.) | Li, Gang (Li, Gang.) (学者:李港) | Xu, Lei (Xu, Lei.)

收录:

EI Scopus PKU CSCD

摘要:

According to color and geometric properties of traffic signs in our country, an efficient traffic sign recognition system applying to natural scenes is proposed in this paper. In this system, an improved image segmentation algorithm based on RGB model is implemented on segmenting traffic signs in natural scenes. Moreover, two level neural networks are used to classify and recognize traffic signs. The outline and invariable moment characteristics are used as the input characteristics of the classification neural network and identification neural network, respectively. The experimental results demonstrate this efficient system can achieve perfect reorganization results to traffic signs in natural sciences; furthermore, it's robust and broad applicability.

关键词:

Image enhancement Image segmentation Neural networks Pattern recognition Traffic signs

作者机构:

  • [ 1 ] [Sun, Guang-Min]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Wang, Jing]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Yu, Guang-Yu]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Li, Gang]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 5 ] [Xu, Lei]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

通讯作者信息:

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2010

期: 10

卷: 36

页码: 1337-1343,1395

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次:

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 4

在线人数/总访问数:200/3603407
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司