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Extracting Auto-Correlation Feature for License Plate Detection Based on AdaBoost
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Extracting Auto-Correlation Feature for License Plate Detection Based on AdaBoost
Hauchun Tan5 , Yafeng Deng6 and Hao Chen5
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Deparment of Transportation Engineering, Beijing Institute of Technology, Beijing, 100084, China |
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Vimicro Corp., Beijing, 100083, China |
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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