A Face Recognition Approach Based on Nearest Neighbor Interpolation and Local Binary Pattern

被引：1

作者：

Aizan, Josky ^{[1
]}

Ezin, Eugene C. ^{[1
,2
]}

Motamed, Cina ^{[3
]}

机构：

[1] Univ Abomey Calavi, Inst Format & Rech Informat, BP 526, Cotonou, Benin

[2] Univ Abomey Calavi, Inst Mat & Sci Phys, BP 526, Cotonou, Benin

[3] Univ Littoral Cote Opale France, Lab Informat Signal & Image Cote Opale, 50 Rue F Buisson,BP 719, F-62228 Calais, France

来源：

2016 12TH INTERNATIONAL CONFERENCE ON SIGNAL-IMAGE TECHNOLOGY & INTERNET-BASED SYSTEMS (SITIS) | 2016年

关键词：

Face recognition; Dimensionality reduction; Local Binary Pattern;

D O I：

10.1109/SITIS.2016.21

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we present a novel approach for face recognition which consists of a dimensionality reduction of face feature vectors. The image scaling is firstly conducted on an input face image. Then we applied the Local Binary Pattern (LBP) operator by dividing the face image into non-overlapped regions. LBP histograms are extracted from each region and concatenated into a single one that represents the face image. Nearest neighbor classifier is used to perform recognition with Chi square function as a dissimilarity measure. Simulation experiments are done using the ORL (Olivetti Research Laboratory) database showing the efficiency of the proposed approach with 97.5% as recognition rate.

引用

页码：76 / 81

页数：6

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