首页> 外文会议>Conference on Medical Imaging 2008: Imaging Processing; 20080217-19; San Diego,CA(US) >Personal Identification Based on Blood Vessels of Retinal Fundus Images
【24h】

Personal Identification Based on Blood Vessels of Retinal Fundus Images

机译:基于视网膜眼底图像血管的个人识别

获取原文
获取原文并翻译 | 示例

摘要

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10~(-5)% and 4.3×10~(-5)%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.
机译:已经实现了生物识别技术,而不是传统的识别方法,例如计算机中的密码,自动柜员机(ATM)以及出入境管理系统。我们建议使用每个人都独有的彩色视网膜眼底图像的个人识别(PI)系统。所提出的识别程序基于数据库中输入眼底图像与参考眼底图像的比较。在第一步中,执行输入图像和参考图像之间的配准。该步骤包括平移和旋转运动。 PI基于从输入图像和参考图像生成的血管图像之间的相似性度量。相似度被定义为根据像素值计算出的互相关系数。当相似度大于预定阈值时,识别输入图像。这意味着输入图像和参考图像都关联到同一个人。包括41个同一个人的图像对在内的462个眼底图像被用于估计所提出的技术。错误拒绝率和错误接受率分别为9.9×10〜(-5)%和4.3×10〜(-5)%。结果表明,所提出的方法具有比DNA以外的其他生物特征更高的性能。为了在公众中实际应用,需要一种能够容易地拍摄眼底图像的装置。所提出的方法不仅适用于PI,而且还适用于警告医疗设施中眼底图像误装的系统。

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