[1]朱长水,丁 勇,袁宝华,等.融合LBP和LPQ的人脸识别[J].南京师大学报(自然科学版),2015,38(01):104.
 Zhu Changshui,Ding Yong,Yuan Baohua,et al.Face Recognition Based on Local Binary Patternand Local Phase Quantization[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(01):104.
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融合LBP和LPQ的人脸识别()
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《南京师大学报》(自然科学版)[ISSN:1001-4616/CN:32-1239/N]

卷:
第38卷
期数:
2015年01期
页码:
104
栏目:
计算机科学
出版日期:
2015-06-30

文章信息/Info

Title:
Face Recognition Based on Local Binary Patternand Local Phase Quantization
作者:
朱长水丁 勇袁宝华曹红根
南京理工大学泰州科技学院,江苏 泰州 225300
Author(s):
Zhu ChangshuiDing YongYuan BaohuaCao Honggen
Taizhou Institute of Science and Technology,Nanjing University of Science and Technology,Taizhou 225300,China
关键词:
局部二值模式局部相位量化人脸识别
Keywords:
local binary patternlocal phase quantizationface recognition
分类号:
TP
文献标志码:
A
摘要:
空域和频域分析是图像分析的重要方法,提出一种融合空域的局部二值模式(local binary pattern,LBP)和频域的局部相位量化(local phase quantization,LPQ)进行人脸识别的方法. 该方法首先对人脸图像分别在空域提取LBP特征和频域提取LPQ特征,然后融合成LBP/LPQ直方图,进行直方图相似性比较,最后根据最近邻原则进行识别. 在YALE和AR标准人脸数据库上的实验表明,该方法得到的结果比单个方法效果更好,鲁棒性更高.
Abstract:
Spatial and frequency domain analysis is an important method of image analysis. This paper presents a method of face recognition based on local binary pattern and local phase quantization. First,LBP operator is used to extract LBP feature in the spatial domain and LPQ operator is used to extract LPQ feature in the frequency domain from block grey-level face images. Then fused into LBP/LPQ histograms and evaluated the goodness between tow LBP/LPQ histograms. Finally,Face recognition based on the nearest neighbor principle. The simulation experiments illustrate that this method has better recognition rate and more robust than single method on the YALE and AR face database.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-08-20.
基金项目:国家自然科学基金(61101197/F010402).
通讯联系人:朱长水,讲师,硕士,研究方向:虚拟现实、图像处理. E-mail:shui_zc@163.com
更新日期/Last Update: 2015-03-30