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

被引：0

作者：

Tan, Hauchun ^{[1
]}

Den, Yafeng ^{[2
]}

Chen, Hao ^{[1
]}

机构：

[1] Beijing Inst Technol, Dept Transportat Engn, Beijing 100084, Peoples R China

[2] Vimicro Corp, Beijing 100083, Peoples R China

来源：

INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2008 | 2008年 / 5326卷

关键词：

AdaBoost; License Plate Detection; Auto-Correlation;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new method for license plate detection based oil 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.

引用

页码：72 / +

页数：3

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