19 January 2009 Selecting frequency feature for license plate detection based on AdaBoost
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Abstract
In this paper, a new method for license plate detection based on AdaBoost is proposed. In the new method, character frequency feature, which is powerful feature for detecting license plate character, are introduced to feature pool. The frequency features obtained from the FFT of horizontal projection of binary image are selected by AdaBoost. Then, Haar-like features selected by AdaBoost are used to capture subtle structure of license plate. Furthermore, considering the characteristic of Chinese license plate that there are two types of license plate: deeper background-lighter character and lighter background-deeper character license plates, two detectors are designed to extract different license plates respectively. Experimental results show the efficiency of the proposed method.
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Huachun Tan, Huachun Tan, Hao Chen, Hao Chen, Yafeng Deng, Yafeng Deng, Junhui Liu, Junhui Liu, } "Selecting frequency feature for license plate detection based on AdaBoost", Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571O (19 January 2009); doi: 10.1117/12.806082; https://doi.org/10.1117/12.806082
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