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Iris Recognition Using Fourier-Wavelet Features

机译:使用傅立叶小波特征的虹膜识别

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摘要

This paper presents an effective iris recognition system for iris localization, feature extraction, and matching. By combining the shift-invariant and the multi-resolution properties from Fourier descriptor and wavelet transform, the Fourier-Wavelet features are proposed for iris recognition. A similarity measure is adopted as the matching criterion. Four wavelet filters containing Haar, Daubechies-8, Biorthogonal 3.5, and Biorthogonal 4.4 are evaluated and they all perform better than the feature of Gaussian-Hermite moments. Experimental results demonstrate that the proposed features can provide promising performance for iris recognition.
机译:本文提出了一种有效的虹膜识别系统,用于虹膜定位,特征提取和匹配。通过结合傅立叶描述子和小波变换的位移不变性和多分辨率特性,提出了用于虹膜识别的傅立叶小波特征。采用相似性度量作为匹配准则。对包含Haar,Daubechies-8,Biorthogonal 3.5和Biorthogonal 4.4的四个小波滤波器进行了评估,它们的性能都比高斯-赫尔米特矩特征更好。实验结果表明,提出的功能可以为虹膜识别提供有希望的性能。

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