基于对角线性判别分析的虹膜纹理表示与分类

E. Assunção, J. R. Pereira, M. Costa, C. Filho, Rafael Padilla
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引用次数: 1

摘要

子空间方法常用于模式识别问题,其目的是通过确定空间的投影向量来降低空间维数。本文提出了用于虹膜图像特征提取的子空间方法,即二维线性判别分析(2DLDA)、对角线性判别分析(DiaLDA)及其组合(DiaLDA+2DLDA)。将该方法应用于UBIRIS图像数据库,实验结果表明,DiaLDA+2DLDA在识别精度上优于2DLDA方法。这两种方法在降维和阶级区分方面都很强大。
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Representation and classification of iris textures based on diagonal linear discriminant analysis
Subspace methods are frequently used in pattern recognition problems aiming to reduce space dimension by determining its projection vectors. This paper presents subspace methods for feature extraction in an iris image called two-dimensional linear discriminant analysis (2DLDA), diagonal linear discriminant analysis (DiaLDA) and their combination (DiaLDA+2DLDA). The methods were applied in an UBIRIS image database, and the experimental results showed that DiaLDA+2DLDA overcame the 2DLDA method in recognition accuracy. Both methods are powerful in terms of dimension reduction and class discrimination.
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