• DocumentCode
    1070482
  • Title

    Automatic License-Plate Location and Recognition Based on Feature Salience

  • Author

    Chen, Zhen-Xue ; Liu, Cheng-Yun ; Chang, Fa-Liang ; Wang, Guo-You

  • Author_Institution
    Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
  • Volume
    58
  • Issue
    7
  • fYear
    2009
  • Firstpage
    3781
  • Lastpage
    3785
  • Abstract
    License-plate recognition plays an important role in numerous applications, and a number of techniques have been proposed. In this paper, a novel method to recognize license plates is presented. First, the license plates are located using salient features. Then, each of the seven characters in a license plate is segmented. Finally, the character recognizer extracts some salient features of the characters and uses a feature-salience classifier to achieve robust recognition results. In the experiments, 1176 images that were taken from various scenes and conditions were used, and 32 images out of the 1176 images failed to correctly locate the license plates, which amounts to a success rate of 97.3%. In the experiments on identifying license characters, we used 1144 images, for which license plates have successfully been located and out of which 49 images failed to identify the characters; the rate of successful identification is 95.7%. Combining the preceding two rates, the overall rate of success of the developed method is 93.1%.
  • Keywords
    character recognition; image recognition; traffic engineering computing; automatic license-plate location; automatic license-plate recognition; character recognition; feature salience; Feature salience; feature selection; license-plate location; license-plate recognition (LPR);
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2009.2013139
  • Filename
    4752798