• DocumentCode
    2149029
  • Title

    Simplified Local Binary Pattern Descriptor for Character Recognition of Vehicle License Plate

  • Author

    Liu, Lixia ; Zhang, Honggang ; Feng, Aiping ; Wan, Xinxin ; Guo, Jun

  • Author_Institution
    Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2010
  • fDate
    7-10 Aug. 2010
  • Firstpage
    157
  • Lastpage
    161
  • Abstract
    Local Binary Pattern (LBP) is a powerful texture descriptor for its tolerance against illumination changes and its computational simplicity. The basic LBP encodes 256 feature patterns in a 3×3 neighborhood, but not all the patterns are effective for classification. In this paper, we propose a simplified LBP(S-LBP) which produces optimal patterns by using the best coding principle for classification. Meanwhile, we combine S-LBP and Mahalonobis distance in solving the practical problem of character recognition in Chinese license plate. Experimental results demonstrate the effectiveness of our method for vehicle license recognition comparing with other popular methods.
  • Keywords
    character recognition; image classification; image coding; image texture; Chinese license plate; Mahalonobis distance; character recognition; coding principle; computational simplicity; local binary pattern descriptor; simplified-local binary pattern; texture descriptor; vehicle license plate; Character recognition; Feature extraction; Histograms; Licenses; Pixel; Vehicles; Entropy; S-LBP; character recognition; low-resolution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Graphics, Imaging and Visualization (CGIV), 2010 Seventh International Conference on
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    978-1-4244-7840-8
  • Type

    conf

  • DOI
    10.1109/CGIV.2010.32
  • Filename
    5576211