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A performance Evaluation of Shape and Texture based methods for Vein Recognition

机译:基于形状和纹理的静脉识别方法的性能评估

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摘要

This paper gives fair comparisons of shape and texture based methods for vein recognition. The shape of the back of hand contains information that is capable of authenticating the identity of an individual. In this paper, two kinds of shape matching method are used, which are based on Hausdorff distance and Line Edge Mapping(LEM) methods. The vein image also contains valuable texture information, and Gabor wavelet is exploited to extract the discriminative feature. In order to evaluate the system performance, a dataset of 100 persons of different ages above 16 and of different gender, each has 5 images per person is used. Experimental results show that Hausdorff, LEM and Gabor based methods achieved 58%, 66%, 80% individually.
机译:本文对基于形状和纹理的静脉识别方法进行了比较。手背的形状包含能够验证个人身份的信息。本文采用基于Hausdorff距离和线边缘贴图(LEM)方法的两种形状匹配方法。静脉图像还包含有价值的纹理信息,并且利用Gabor小波提取判别特征。为了评估系统性能,使用了一个由100个年龄在16岁以上,性别不同的人组成的数据集,每个人每人有5张图像。实验结果表明,基于Hausdorff,LEM和Gabor的方法分别达到58%,66%和80%。

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