基于局部特征的驾驶证自动识别系统-《郑州大学学报(工学版)》

文章信息/Info

Author(s):: Maling1; Jiang Huiqin1; Liu Yumin2; 1. School of Information Engineering, Zhengzhou University, Zhengzhou 450001, Henan ;2. Research Center of Digital Imaging Technology, Zhengzhou University, Zhengzhou 450001, Henan

Keywords:: texture elimination; binarization; image segmentation; blob analysis; character recognition

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.

Abstract:: 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.