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一种基于2D-PLDA和小波子带的虹膜识别算法

DOI: 10.11834/jig.20110102

Keywords: 虹膜识别,2D-LDA,2D-PLDA,小波子带,特征矩阵

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Abstract:

近年来,基于线性判别分析(LDA)的图像模式识别方法研究越来越受到人们的关注。然而LDA方法自身存在的小样本难题,极大的影响了样本集特征矩阵的获取。研究者随后提出的2维线性分析(2D-LDA)在一定程度上解决了这个问题。在传统2D-LDA基础上,提出一种改进的2维线性分析方法――2D-PLDA,该方法通过对样本集进行预分类,使得散布矩阵更加合理;在此基础上将2D-PLDA和离散小波相结合,应用于虹膜识别中。实验结果证明,该算法在识别精度和计算复杂度等方面均较传统LDA和2D-LDA方法有很大的改进,同时采用小波的不同子带作为输入空间也在一定程度上增加了算法的鲁棒性。

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