信阳师范学院学报（自然科学版）2013，Vol.26Issue(1)：133-135,139,4.DOI:10.3969/j.issn.1003-0972.2013.01.031
LPQ与NMF特征融合的人脸识别
Face Recognition Based on LPQ and NMF
摘要
Abstract
A method of face recognition based on local phase quantization (LPQ) and non-negative matrix factorization (NMF) was proposed. Firstly, LPQ operator was used to extract the LPQ Histogram Sequence (LPQHS) from block face images. According to the contribution of each face block, weight LPQ Histogram Sequence ( Weight LPQHS) was obtained. Secondly, NMF was applied to weight LPQHS for extracting non-negative subspace and the corresponding coefficient matrices. Finally, nearest neighbor principle was utilized in face recognition. The simulation experiments illustrated that this method had better recognition rate on the AR and YALE standard face database.关键词
局部相位量化(LPQ)/非负矩阵分解(NMF)/人脸识别Key words
local phase quantization( LPQ) / non-negative matrix factorization( NMF) / face recognition分类
信息技术与安全科学引用本文复制引用
朱长水,袁宝华,曹红根,袁红星..LPQ与NMF特征融合的人脸识别[J].信阳师范学院学报（自然科学版）,2013,26(1):133-135,139,4.基金项目
国家自然科学基金项目(60875010) （60875010）
