首页> 外文期刊>International journal of computer science and network security >Passport Recognition Using Enhanced ART2-based RBF Neural Networks
【24h】

Passport Recognition Using Enhanced ART2-based RBF Neural Networks

机译:使用基于ART2的增强型RBF神经网络进行护照识别

获取原文
           

摘要

The judgment of forged passports plays an important role in the immigration control system and requires the automatic recognition of passports as the pre-phase processing. This paper, for the recognition of passports, proposed a novel method using the enhanced RBF network based on ART2. The proposed method extracts code sequence blocks and individual codes by applying the Sobel masking, the smearing and the contour tracking algorithms in turn to passport images. The enhanced RBF network was proposed and used for the recognition of individual codes that applies the ART2 algorithm to the learning structure of the middle layer. The experiment results showed that the proposed method has superior in performance in the recognition of passport.
机译:伪造护照的判断在出入境控制系统中起着重要作用,并且需要自动识别护照作为前期处理。为了识别护照,本文提出了一种基于ART2的增强RBF网络的新方法。所提出的方法通过依次对护照图像应用Sobel蒙版,拖尾和轮廓跟踪算法来提取代码序列块和单个代码。提出了增强的RBF网络,并将其用于将ART2算法应用于中间层的学习结构的单个代码的识别。实验结果表明,该方法在护照识别方面具有优越的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号