基于局部特征的驾驶证自动识别系统  

Automatic Recognition System of Driver's License Based on Local Features

作　　者：马岭[1,2] 蒋慧琴[1,2] 刘玉敏[2,3] 

机构地区：[1]郑州大学信息工程学院,河南郑州450001 [2]郑州大学数字化影像技术研究中心,河南郑州450001 [3]郑州大学商学院,河南郑州450001

出　　处：《郑州大学学报（工学版）》2017年第5期13-17,22,共6页Journal of Zhengzhou University（Engineering Science）

基　　金：国家自然科学基金-河南联合基金重点支持项目(U1604262);国家自然科学基金资助项目(71672182)

摘　　要：针对待识别号码存在于文字、阴影线、方框等实际复杂背景中时,现有算法识别精度低、普适性及鲁棒性不强等问题,设计并实现了一种高速驾驶证自动识别系统.首先通过自适应二值化与形态学处理相结合解决因光照不匀、噪声、倾斜及具有阴影线字符导致的分割难点,进而利用Blob分析提取驾驶证上的重要局部特征,最后综合利用字符先验信息和相关匹配算法提高识别率.实际测试结果表明,系统识别率高,并据此开发出了投向市场的实用产品.In order to meet the practical requirements of automatic application and renewal of driver＇s license,a high speed system for automatic recognition of driver＇s licenser was designed and implemented. The hardware was designed to capture the image of the driver＇s license that contained the smallest identifiable features. Because of the complex background such as the shadow line and so on in the driver＇s license images,the existing recognition algorithms had the low recognition accuracy,universality and robustness problems. This paper first solved the segmentation difficulties for uneven illumination,noise,tilt and shadow line character by combined adaptive binarization and morphological processing. Then,the Blob analysis was used to extract the important local features of the driver＇s license,and the recognition accuracy was further improved by using the prior information and the correlation matching algorithm. The experimental results showed that not only the false recognition rate was 0,but also the practical products was developed,and the better social effects were achieved.

关 键 词：纹理消除 二值化 图像分割 BLOB分析 字符识别 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]