Face Recognition via Lorentzian Metric

被引:0
|
作者
Kerimbekov, Yerzhan [1 ]
Bilge, Hasan Sakir [2 ]
机构
[1] Ahmet Yesevi Univ, Bilgisayar Muhendisligi, Ankara, Turkey
[2] Gazi Univ, Elekt Elekt Muhendisligi Bolumu, Ankara, Turkey
来源
2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2017年
关键词
Face recognition; Lorentz metric; feature selection; CLASSIFICATION;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Nowadays the face recognition applications are extremely important in terms of information security. In this study, a new Lorentz Face Recognition (LFR) method based on special properties of Lorentz space was developed. The proposed method produces a similarity value for new test sample according to Lorentz distance. A similarity value is determined by nearest neighbor method as 1 or 0, namely, the true or false face image respectively. Moreover, we propose the Lorentz Feature Selection (LFS) based on Lorentz metric. The LFS is used for dimensionality reduction and to increase recognition accuracy of proposed method in multidimensional face data. The experimental results taken from face data sets show that the proposed LFR method is usable.
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页数:4
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