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Proceedings Paper

Selecting frequency feature for license plate detection based on AdaBoost
Author(s): Huachun Tan; Hao Chen; Yafeng Deng; Junhui Liu
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Paper 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.

Paper Details

Date Published: 19 January 2009
PDF: 6 pages
Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571O (19 January 2009); doi: 10.1117/12.806082
Show Author Affiliations
Huachun Tan, Beijing Institute of Technology (China)
Hao Chen, Beijing Institute of Technology (China)
Yafeng Deng, Vimicro Corp. (China)
Junhui Liu, Institute of Logistics Equipment for China Armed Police Force (China)

Published in SPIE Proceedings Vol. 7257:
Visual Communications and Image Processing 2009
Majid Rabbani; Robert L. Stevenson, Editor(s)

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