• DocumentCode
    3364693
  • Title

    Empirical analysis of AdaBoost algorithms on license plate detection

  • Author

    Sun, Junxi ; Cui, Dong ; Gu, Dongbing ; Hua Cai ; Liu, Guangwen

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Changchun Univ. of Sci. & Technol., Changchun, China
  • fYear
    2009
  • fDate
    9-12 Aug. 2009
  • Firstpage
    3497
  • Lastpage
    3502
  • Abstract
    AdaBoost algorithm is an effective license plate detection method in the field of license plate recognition technology. A through analysis of three boosting algorithms (namely Discrete, Real and Gentle AdaBoost) is presented for license plate detection, including the algorithm details and experiment comparisons. The experimental results show the Gentle AdaBoost algorithm obtains an overall better results in terms of high detection rate and low false positive rate than the discrete AdaBoost algorithm or real AdaBoost algorithm.
  • Keywords
    image recognition; AdaBoost algorithms empirical analysis; license plate detection; license plate recognition technology; Algorithm design and analysis; Automation; Boosting; Information analysis; Iterative algorithms; Layout; Licenses; Object detection; Object recognition; Sun; AdaBoost algorithm; License plate detection; weak classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation, 2009. ICMA 2009. International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-2692-8
  • Electronic_ISBN
    978-1-4244-2693-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2009.5246285
  • Filename
    5246285