...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Machine Vision and Applications >A new multi-unit iris authentication based on quality assessment and score level fusion for mobile phones
【24h】

A new multi-unit iris authentication based on quality assessment and score level fusion for mobile phones

机译：基于质量评估和分数等级融合的手机多单元虹膜认证

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

Although iris recognition technology has been reported to be more stable and reliable than other biometric systems, performance can be degraded due to many factors such as small eyes, camera defocusing, eyelash occlusions and specular reflections on the surface of glasses. In this paper, we propose a new multi-unit iris authentication method that uses score level fusion based on a support vector machine (SVM) and a quality assessment method for mobile phones. Compared to previous research, this paper presents the following two contributions. First, we reduced the false rejection rate and improved iris recognition accuracy by using iris quality assessment. Second, if even two iris images were determined to be of bad quality, we captured the iris images again without using a recognition process. If only one iris image among the left and right irises was regarded as a good one, it was used for recognition. However, if both the left and right iris images were good, we performed multi-unit iris recognition using score level fusion based on a SVM. Experimental results showed that the accuracy of the proposed method was superior to previous methods that used only one good iris image or those methods that used conventional fusion methods.
机译：尽管据报道虹膜识别技术比其他生物识别系统更稳定和可靠，但是由于许多因素，例如小眼睛，相机散焦，睫毛遮挡和眼镜表面的镜面反射，性能可能会下降。在本文中，我们提出了一种新的基于支持向量机（SVM）的基于分数等级融合的多单元虹膜认证方法和一种用于手机的质量评估方法。与以前的研究相比，本文提出了以下两个方面的贡献。首先，我们通过使用虹膜质量评估降低了错误拒绝率并提高了虹膜识别精度。其次，即使确定两个虹膜图像质量较差，我们也无需使用识别过程就可以再次捕获虹膜图像。如果左右虹膜中只有一个虹膜图像被认为是好图像，则将其用于识别。但是，如果左虹膜图像和右虹膜图像均良好，我们将使用基于SVM的得分水平融合来执行多单元虹膜识别。实验结果表明，该方法的准确性优于仅使用一个良好虹膜图像的先前方法或使用常规融合方法的方法。

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