基于级联卷积网络的自然场景下的车牌检测

被引：5

作者：

闫鹏

牛常勇

范明

机构：

[1] 郑州大学信息工程学院

来源：

计算机工程与设计 | 2014年 / 35卷 / 12期

关键词：

车牌检测; 卷积网络; 级联分类器; 自然场景; 误报率;

D O I：

10.16208/j.issn1000-7024.2014.12.043

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

为有效解决自然场景下车牌检测的分类效率和分类准确率之间的矛盾,提出一种鲁棒的快速车牌检测方法。以整个车牌作为训练和检测的基本单位,直接使用卷积网络作为检测器,级联多个卷积网络,对自然场景下的车牌进行检测。通过引入卷积网络作为基本的学习子单元,进一步把多个子单元组织成级联结构,满足了自然场景下的车牌检测对检测准确率和检测效率的要求。在现实数据上的实验结果表明,级联卷积网络在保证较低误报率的同时具有较高的检测率和检测效率。

引用

页码：4296 / 4301

页数：6

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