• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Soft Computing and Pattern Recognition >Agent-based Two-dimensional Barcode Decoding Robust against Non-uniform Geometric Distortion
【24h】

Agent-based Two-dimensional Barcode Decoding Robust against Non-uniform Geometric Distortion

机译：基于代理的二维条形码解码鲁棒免受非均匀几何失真

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Two-dimensional (2D) codes are assumed to be printed on flat planes and subject to distortion when printed on non-rigid materials such as papers and clothes. Although general 2D code decoders correct uniform distortion such as perspective distortion, it is difficult to correct non-uniform and irregular distortion of 2D code itself. To cope with this problem, this paper proposes an agent-based approach to reconstruct 2D code. In this approach, auxiliary lines are given to a 2D code and used to recognize the distortion. First, the proposed method finds 2D code area using feature patterns composed by the auxiliary lines, and looks for finder patterns by Convolutional Neural Network (CNN). Then, many agents simultaneously trace the lines referring various image features and neighborhood agents. Feature weights are optimized by Genetic Algorithm. Experimental results showed that the proposed method has prospects that it can decode distorted 2D code without occlusion.
机译：假设二维（2D）码在平面上印刷，并且在印刷在诸如纸和衣服的非刚性材料上时受到失真。虽然一般的2D代码解码器正确均匀失真，例如透视失真，但难以校正2D代码本身的不均匀和不规则的失真。要应对这个问题，本文提出了一种基于代理的方法来重建2D代码。在这种方法中，辅助线被给予2D代码并用于识别失真。首先，该方法使用由辅助线组成的特征模式找到2D代码区域，并通过卷积神经网络（CNN）查找查找发现器模式。然后，许多代理同时追踪指示各种图像特征和邻域代理的线。特征权重通过遗传算法进行优化。实验结果表明，该方法具有前景，它可以解码扭曲的2D代码而无需闭塞。

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