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ZHANG Xiao-na, HE Ren, CHEN Shi-an, YAO Ming. Vehicle license plate location using active learning AdaBoost algorithm and color feature[J]. Journal of Traffic and Transportation Engineering, 2013, 13(1): 121-126. doi: 10.19818/j.cnki.1671-1637.2013.01.018
Citation: ZHANG Xiao-na, HE Ren, CHEN Shi-an, YAO Ming. Vehicle license plate location using active learning AdaBoost algorithm and color feature[J]. Journal of Traffic and Transportation Engineering, 2013, 13(1): 121-126. doi: 10.19818/j.cnki.1671-1637.2013.01.018
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Vehicle license plate location using active learning AdaBoost algorithm and color feature

doi: 10.19818/j.cnki.1671-1637.2013.01.018

  • School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, Jiangsu, China

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  • Author Bio:

    ZHANG Xiao-na(1981-), female, lecturer, doctoral student, +86-511-88780270, xnzhang@ujs.edu.cn

    HE Ren(1962-), male, professor, PhD, +86-511-88780270, heren@ujs.edu.cn

  • Received Date: 2012-07-14
  • Publish Date: 2013-02-25
    Abstract
  • A small amount of license plate areas and non-license plate areas were selected, and Haar-like extended features were extracted by using the integration diagram method to obtain initial training samples. An initial classifier was generated by training the samples with AdaBoost algorithm. A strong classifier for license plate detection was obtained in the active learning procedure. The coarse location of license plate was implemented by using the cascade structure detection method. The candidate region was verified to get the precise location of license plate area by extracting edge-color pairs. The method was applied into the test of vehicle license plate location under different illumination and defaced circumstances. Test result indicates that the coarse location rate of license plate is 98.3%, the precise location rate is 97.1%, and the average location time is less than 0.1 s. A better license plate location effect and accuracy are achieved by the proposed method.

     

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