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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.)

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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

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来源 :

Journal of Beijing University of Technology

ISSN: 0254-0037

年份: 2010

期: 10

卷: 36

页码: 1337-1343,1395

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