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A Novel Approach for License Plate Recognition Using Subspace Projection and Probabilistic Neural Network

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Book cover Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

License plate recognition has many applications in traffic systems. It is very difficult because images are usually noisy, broken or incomplete. In this paper, a novel robust approach for license plate recognition is proposed, which combines subspace projection with probabilistic neural network to improve the recognition rate. Probabilistic neural network is used as a classifier to identify low-dimension test samples which are obtained from actual license plate images by subspace projection. Experiment results show the effectiveness of the proposed method.

Research mainly supported by the NSFC (No. 60375004).

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References

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Author information

Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, 100084, China

    Yafeng Hu, Feng Zhu & Xianda Zhang

Authors
  1. Yafeng Hu
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  2. Feng Zhu
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  3. Xianda Zhang
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Hu, Y., Zhu, F., Zhang, X. (2005). A Novel Approach for License Plate Recognition Using Subspace Projection and Probabilistic Neural Network. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_34

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  • DOI: https://doi.org/10.1007/11427445_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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