Efficient k-class approach for face recognition

被引：7

作者：

Alqudah, Amin ^{[1
]}

Al-Zoubi, Hussein ^{[1
]}

机构：

[1] Yarmouk Univ, Hijjawi Fac Engn Technol, Dept Comp Engn, Irbid 21163, Jordan

来源：

COMPUTERS & ELECTRICAL ENGINEERING | 2015年 / 45卷

关键词：

Face detection; Face recognition; Recognition rate; Self-organizing-maps; GABOR WAVELETS; KERNEL PCA; IMAGE; REPRESENTATION; FEATURES; MODEL; VERIFICATION; HISTOGRAM; SELECTION; MOMENTS;

D O I：

10.1016/j.compeleceng.2015.03.031

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this research work, a new k-class approach for efficient and accurate face recognition called kCAFRe is established. The kCAFRe system has three stages: preprocessing, training, and testing. In the training phase, four reference pictures (classes) are constructed for each person. During testing, the correlation coefficient (CC) is calculated between the picture under test and each of the reference pictures. For each person, one accredited class is chosen. Subsequently, the accredited class for the person with the highest CC is selected. Results were given for four image databases. A recognition ratio of 97% has been obtained for the Libor Spacek's set. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：260 / 273

页数：14

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