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International Conference on Neural Information Processing

ICONIP 2012: Neural Information Processing pp 100–108Cite as

Vehicle License Plate Localization and License Number Recognition Using Unit-Linking Pulse Coupled Neural Network

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7667))

Abstract

In this paper, Unit-linking Pulse Coupled Neural Network (U-PCNN) is applied in vehicle license Plate Localization (PL) and license Number Recognition (NR) being part of optical character recognition(OCR). PL and NR are cores of License Plate Recognition (LPR) system. In PL, firstly, the proposed algorithm based on U-PCNN edge detection highlights plate regions, and then using those results obtains plate locations. In NR, employing U-PCNN extracts features of license number. The experimental results show that the license plates properly extracted were 224 over 233 input images (96.137%) and the NR accuracy is 96.67%.

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References

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering, Fudan University, 220 Handan Road, Shanghai, 200433, P.R. China

    Ya Zhao & Xiaodong Gu

Authors
  1. Ya Zhao
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  2. Xiaodong Gu
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zhao, Y., Gu, X. (2012). Vehicle License Plate Localization and License Number Recognition Using Unit-Linking Pulse Coupled Neural Network. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_13

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  • DOI: https://doi.org/10.1007/978-3-642-34500-5_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34499-2

  • Online ISBN: 978-3-642-34500-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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