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Extracting Auto-Correlation Feature for License Plate Detection Based on AdaBoost

  • Hauchun Tan
  • Yafeng Deng
  • Hao Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5326)

Abstract

In this paper, a new method for license plate detection based on AdaBoost is proposed. In the proposed method, auto-correlation feature, which is ignored by previous learning-based method, is introduced to feature pool. Since that there are two types of Chinese license plate, one type is deeper-background-lighter-character and the other is lighter-background-deeper-character, training a detector cannot convergent. To avoid this problem, two detectors are designed in the proposed method. Experimental results show the superiority of proposed method.

Keywords

AdaBoost License Plate Detection Auto-Correlation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hauchun Tan
    • 1
  • Yafeng Deng
    • 2
  • Hao Chen
    • 1
  1. 1.Deparment of Transportation EngineeringBeijing Institute of TechnologyBeijingChina
  2. 2.Vimicro Corp.BeijingChina

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