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首页> 外文期刊>Biocybernetics and biomedical engineering >A retinal image authentication framework based on a graph-based representation algorithm in a two-stage matching structure
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A retinal image authentication framework based on a graph-based representation algorithm in a two-stage matching structure

机译：基于基于图的两级匹配结构的基于图形表示算法的视网膜图像认证框架

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摘要

Abstract Retinal vascular pattern has many valuable characteristics such as uniqueness, stability and permanence as a basis for human authentication in security applications. This paper presents an automatic rotation-invariant retinal authentication framework based on a novel graph-based retinal representation scheme. In the proposed framework, to replace the retinal image with a relational mathematical graph (RMG), we propose a novel RMG definition algorithm from the corresponding blood vessel pattern of the retinal image. Then, the unique features of RMG are extracted to supplement the authentication process in our framework. The authentication process is carried out in a two-stage matching structure. In the first stage of this scenario, the defined RMG of enquiry image is authenticated with enrolled RMGs in the database based on isomorphism theory. If the defined RMG of enquiry image is not isomorphic with none enrolled RMG in the database, in the second stage of our matching structure, the authentication is performed based on the extracted features from the defined RMG by a similarity-based matching scheme. The proposed graph-based authentication framework is evaluated on VARIA database and accuracy rate of 97.14% with false accept ratio of zero and false reject ratio of 2.85% are obtained. The experimental results show that the proposed authentication framework provides the rotation invariant, multi resolution and optimized features with low computational complexity for the retina-based authentication application.
机译：摘要视网膜血管模式具有许多有价值的特性，如唯一性，稳定性和持久性，作为安全应用中人类认证的基础。本文介绍了基于基于图形的视网膜表示方案的自动旋转不变视网膜认证框架。在所提出的框架中，为了用关系数学图（RMG）更换视网膜图像，我们提出了一种从视网膜图像的相应血管图案的新颖RMG定义算法。然后，提取RMG的独特功能以补充我们的框架中的认证过程。认证过程在两级匹配结构中执行。在这种情况的第一阶段，基于同构理论，通过数据库中的注册RMG认证了定义的询问图像。如果所定义的查询图像没有与数据库中的RMG相同，则在我们的匹配结构的第二阶段，基于由相似性的匹配方案基于来自定义的RMG的提取特征来执行认证。在Varia数据库中评估所提出的基于图形的认证框架，并获得了零误率为2.85％的假接受比率为97.14％的精度。实验结果表明，所提出的认证框架提供了对基于视网膜的身份验证应用程序的旋转不变，多分辨率和优化的功能，具有低计算复杂性。

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