【24h】

Improved and robust eyelash and eyelid location method

机译:改良而坚固的睫毛和眼睑定位方法

获取原文
获取原文并翻译 | 示例

摘要

Iris recognition has been very popular among researchers as an important personal identification technology due to its unique, stable and noninvasive properties. However, because of iris occlusion such as eyelid and eyelashes, high accuracy of iris recognition system is challenged. In this paper, we firstly improve our previous work on eyelashes localization algorithm based on Expectation Maximization (EM) and Gaussian Mixture Model (GMM). Then, we propose a novel and robust approach to search the eyelid via hybrid edge detection and Hough transform, which reduces the noise fitting points and selects the eyelid fitting area automatically. Experimental results reveal our proposal can detect eyelid and eyelashes accurately and effectively.
机译:虹膜识别由于其独特,稳定和无创的特性,作为一种重要的个人识别技术在研究人员中非常受欢迎。然而,由于虹膜闭塞,例如眼睑和睫毛,虹膜识别系统的高精度受到挑战。在本文中,我们首先改进了基于期望最大化(EM)和高斯混合模型(GMM)的睫毛定位算法。然后,我们提出了一种新颖而鲁棒的方法,通过混合边缘检测和霍夫变换来搜索眼睑,该方法减少了噪声拟合点,并自动选择了眼睑拟合区域。实验结果表明我们的建议可以准确有效地检测眼睑和睫毛。

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