Fusing DCT and LBP features for face recognition

被引：0
|
作者：
Li, Jian-Ke [1 ,2 ]
Zhao, Bao-Jun [1 ]
Zhang, Hui [1 ]
Jiao, Ji-Chao [1 ]
机构：
[1] Center for Research on Radar Technology, Beijing Institute of Technology, Beijing 100081, China
[2] College of Information and Technology, Hebei University of Economics and Business, Shijiazhuang, Hebei 050061, China
来源：
Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2010年 / 30卷 / 11期
关键词：
Concatenated codes - Discrete cosine transforms - Face recognition - Graphic methods;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A novel method by fusing discrete cosine transform (DCT) and local binary pattern (LBP) features is proposed for face recognition in this research. The primary information of the face image was centralized in a small number of DCT coefficients, which were used as the frequency feature of the face. The face was divided regularly into small regions, from which LBP code histograms were computed and concatenated into a spatial global histogram used as descriptor vector of the face. The descriptor vector was dimensionally reduced by PCA. Then, the DCT features and the LBP features were fused posterior to the normalization. The experiments on ORL face database show the improvability of the proposed scheme on the methods using just single DCT or LBP feature for face recognition.
引用
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页码：1355 / 1359
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