华东师范大学学报（自然科学版） >

2016 , Vol. 2016 >Issue 4: 77 - 85

DOI: https://doi.org/10.3969/j.issn.1000-5641.2016.04.009

计算机科学

基于LBP和Gabor混合特征的近红外人脸识别

  • 赵骥 ,
  • 童卫青
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  • 华东师范大学 计算机系, 上海200241

收稿日期: 2015-06-12

  网络出版日期: 2016-09-29

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Face recognition using near infrared images based on LBP and Gabor hybrid feature

  • ZHAO Ji ,
  • TONG Wei-qing
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  • Department of Computer Science and Technology, East China Normal University, Shanghai 200241, China

Received date: 2015-06-12

  Online published: 2016-09-29

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摘要

综合局部二值模式（Local Binary Patterns，LBP）和Gabor函数特征的优点，并结合余弦相似度和主元分析(Principal Component Analysis，PCA)方法，提出特征混合的人脸识别算法并研究4种不同的LBP和Gabor特征混合的方法.在871人的近红外人脸图像库上的实验表明，基于LBP和Gabor混合特征的人脸识别方法能获得较高的人脸识别正确率和较低的误识率.

关键词： 人脸识别; LBP; Gabor; 支持向量机

本文引用格式

赵骥 , 童卫青 . 基于LBP和Gabor混合特征的近红外人脸识别[J]. 华东师范大学学报（自然科学版）, 2016 , 2016(4) : 77 -85 . DOI: 10.3969/j.issn.1000-5641.2016.04.009

Abstract

To take advantages of local binary patterns (LBP) and Gabor, we proposed an algorithm for face recognition based on hybrid features, using cosine similarity and principal component analysis (PCA). Four kinds of LBP and Gabor hybrid feature methods were studied and experimental results on 871 people’s nearinfrared face illustrated that the proposed method attained higher correct rate and lower false accept rate (FAR).

Key words： face recognition; LBP; Gabor; support vector machine (SVM)

参考文献

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