视网膜生物识别的形状签名

M. C. Azemin, D. Kumar, H. Wu
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引用次数: 12

摘要

在唯一的商业可用的视网膜生物识别系统中使用的技术是基于对视盘周围的血管结构进行编码。然而,据报道,这种技术具有较低的人际变异性,因此不适合从大型数据库中识别个人。在本文中,我们提出了一种基于形状特征的新技术来量化视网膜结构的轮廓,以增加人与人之间的距离,并减少视盘周围新血管生长的影响。相关性是作为不同眼睛图像之间1560个独特视网膜配对的相似性度量来计算的。该结果是通过一种改进的形状特征技术来量化视网膜结构的轮廓,特别是对于分支状血管。相关性的分布范围从-0.54到0.76,类似于正态分布,平均值为0.09。对平移、旋转、缩放和噪声的影响也进行了研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shape Signature for Retinal Biometrics
The technique used in the only commercially available system for retinal biometrics is based on encoding the vessel structure surrounding the optic disc. However, it has been reported that this technique has low inter-personal variability, making it unsuitable for identifying an individual from a large database. In this paper we propose a new technique based on the shape signature to quantify the contours of the retina structure to increase the inter-personal distance and to lessen the effects of growth of new blood vessels around the optic disc. Correlations are computed as a measure of similarity of 1560 unique retina pairings between different eye images. The results are obtained from a modified shape signature technique of quantifying the contour of the retina structure particularly for the branch-like vessels. The distribution of the correlation, which range from -0.54 to 0.76, resembles a normal distribution with a mean of 0.09. Effects against translation, rotation, scaling and noise are also investigated.
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