计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 264-266.

• 图形图像 • 上一篇    下一篇

虹膜定位算法的研究

史春蕾,金龙旭   

  1. (中国科学院长春光学精密机械与物理研究所 长春130033);(中国科学院研究生院 北京100039)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家863高技术研究发展计划项目(No. 863-2-5-1-13B)资助。

Investigation of the Algorithm for Iris Localization

SHI Chun-lei,JIN Long-xu   

  • Online:2018-12-01 Published:2018-12-01

摘要: 虹膜识别系统中的虹膜定位精度和定位速度影响识别系统性能。在分析现有虹膜识别算法的基础上,采用基于Canny思想的边缘检测算子提取虹膜图像边缘信息,结合先验知识在小图像块上进行Hough变换拟合虹膜内外圆。实验结果表明,该定位方法在保证定位精度的同时有效地提高了定位速度。虹膜区域的噪声包括眼睑、睫毛、眼睑阴影和光斑等,在眼睑定位方面提出了边缘检测结合Radon变换分段直线定位去除眼睑噪声的方法,同时采用阈值法去除了睫毛和眼睑阴影对虹膜区域的干扰,并用实验验证了该算法的有效性和准确性。

关键词: 虹膜定位,边缘提取,霍夫变换,眼睑定位

Abstract: The accuracy and speed of iris boundary localization affect recognition system performance in the iris recognilion system. Based on analyzing some prevailing iris recognition algorithms, the edge information of the iris image was extracted by the edge detection operator which is based on Canny's thought, iris inner circle and outer circle were loca lined by Hough transform within the small block images by incorporating prior knowledge, and experimental result shows that this localization method improves the boundary localization speed and it also ensures the localization accuracy. The yawp from iris region includes the eyelid, eyelash, eyelid shadow and specular reflections. The segmental-secondary linear localization method adopting edge detection and Radon transform was proposed to remove the interference from the eyelid on the eyelid localization, the eyelash yawp and eyelid shadow were removed by threshold method, and experimental result shows that the algorithm is efficient and accurate.

Key words: Iris localization, Edge extraction, Hough transform, Eyelid localization

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