...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Pattern Recognition and Artificial Intelligence >IRIS RECOGNITION OF DEFOCUSED IMAGES FOR MOBILE PHONES
【24h】

IRIS RECOGNITION OF DEFOCUSED IMAGES FOR MOBILE PHONES

机译：虹膜识别的移动电话图像

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this paper, we introduce a novel iris recognition approach for mobile phones, which takes into account imaging noise arising from image capture outside the depth of field (DOF) of cameras. Unlike existing approaches that rely on special hardware to extend the DOF or computationally expensive algorithms to restore the defocused images prior to recognition, the proposed method performs recognition on the defocused images based on the stable bits in the iris code representation that are robust to imaging noise. To the best of our knowledge, our work is the first to investigate the characteristics of iris features for varying degree of image defocus when the images are captured outside the DOF of cameras. Based on our findings, we present a method to determine the stable bits of an enrolled image. When compared to iris recognition of defocused images that relies on the entire code representation, the proposed recognition method increases the inter-class variability while reducing the intra-class variability of the samples considered. This leads to smaller intersections between the intra-class and inter-class distance distributions, which results in higher recognition performance. Experimental results based on over 15,000 images show that the proposed method achieves an average recognition performance gain of about two times. It is envisioned that the proposed method can be incorporated as part of a multi-biometric system for mobile phones due to its lightweight computational requirements, which is well suited for power sensitive solutions.
机译：在本文中，我们介绍了一种新颖的手机虹膜识别方法，该方法考虑了摄像头景深（DOF）之外的图像捕获所产生的成像噪声。与依赖于特殊硬件扩展自由度的现有方法或在识别之前还原散焦图像的计算方法昂贵的算法不同，该方法基于虹膜代码表示中对成像噪声具有鲁棒性的稳定位对散焦图像执行识别。 。据我们所知，我们的工作是第一个研究当在相机的自由度之外捕获图像时可变程度的图像散焦的虹膜特征的特性。基于我们的发现，我们提出一种确定已注册图像的稳定位的方法。当与依赖于整个代码表示的散焦图像的虹膜识别相比时，所提出的识别方法增加了类间的可变性，同时减少了所考虑样本的类内可变性。这导致类内和类间距离分布之间的交点较小，从而导致更高的识别性能。基于15,000多个图像的实验结果表明，该方法实现了约两倍的平均识别性能。可以预见，由于该方法的轻量级计算要求，因此可以作为移动电话的多生物计量系统的一部分，非常适合于功率敏感型解决方案。

著录项

  • 来源
  • 作者

    BO LIU; SIEW-KEI LAM; THAMBIPILLAI SRIKANTHAN; WEIQI YUAN;

  • 作者单位

    Computer Vision Group, Shenyang University of Technology Shenyang, P. R. China, 110870,Centre for High Performance Embedded Systems Nanyang Technological University, Singapore, 637553;

    Centre for High Performance Embedded Systems Nanyang Technological University, Singapore, 637553;

    Centre for High Performance Embedded Systems Nanyang Technological University, Singapore, 637553;

    Computer Vision Group, Shenyang University of Technology Shenyang, P. R. China, 110870;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    iris recognition; defocused iris image; depth of field.;

    机译：虹膜识别;离焦虹膜图像;景深。;

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