Face Recognition using Local Binary Probabilistic Pattern (LBPP) and 2D-DCT Frequency Decomposition

被引：6
|
作者：
Dahmouni, Abdellatif [1 ]
Aharrane, Nabile [1 ]
Satori, Khalid [1 ]
El Moutaouakil, Karim [2 ]
机构：
[1] Sidi Mohamed Ben Abdellah Univ, Fac Sci Dhar Mahraz, LIIAN, Dept Math & Comp Sci, BP 1796 Atlas, Fes, Morocco
[2] Mohamed 1 Univ, ENSAH, Natl Sch Appl Sci, BP 03, Al Hoceima, Morocco
来源：
2016 13TH INTERNATIONAL CONFERENCE ON COMPUTER GRAPHICS, IMAGING AND VISUALIZATION (CGIV) | 2016年
关键词：
LBP; LBPP; Confidence interval and 2D-DCT;
D O I：
10.1109/CGiV.2016.23
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Facial biometrics is an active modality that uses the face characteristics as argument of person identification. In this paper, we propose a new face recognition system basing on the Local Binary Probabilistic Pattern (LBPP) face representation and the global 2D-DCT frequency methods. The Local Binary Probabilistic Pattern is an alternative of the famous LBP descriptor which uses the confidence interval concept to evaluate the current pixel. Then the LBPP transformed images are decomposed in the frequency domain at 2D-DCT method to build a reduce features vector. The suggested approach is tested on ORL and Yale databases. The obtained results are very encouraging: 95.5% for ORL and 100% for Yale databases recognition rate.
引用
收藏
页码：73 / 77
页数：5
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