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

Authors:
Hauchun Tan;Yafeng Deng;Hao Chen
Affiliations:
Deparment of Transportation Engineering, Beijing Institute of Technology, Beijing, China 100084;Vimicro Corp., Beijing, China 100083;Deparment of Transportation Engineering, Beijing Institute of Technology, Beijing, China 100084
Venue:
IDEAL '08 Proceedings of the 9th International Conference on Intelligent Data Engineering and Automated Learning
Year:
2008

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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.