Hybrid of the approximate neural network with sparse RAM and Fisher´s linear discriminant for face recognition

Author

Zhaojie, Zhocj ; Yuxia, Sun ; Lenan, Wu

Author_Institution

Dept. of Radio Eng., Southeast Univ., Nanjing, China

Volume

1

fYear

2003

fDate

14-17 Dec. 2003

Firstpage

212

Abstract

In this paper, a face recognition approach based on the hybrid of the approximate neural network with sparse RAM (SN-tuple) and Fisher´s linear discriminant (FLD) is presented. Firstly, the data of original face images are imported into the SN-tuple to classify these faces roughly. Then FLD, a classical statistical pattern recognition method, are used to classify these faces precisely. Experimental results demonstrate that this proposed approach achieves better performance than the SN-tuple and FLD for face recognition respectively.

Keywords

face recognition; image classification; neural nets; statistics; approximate neural network; face images; face recognition approach; linear discriminant; random access memory; sparse RAM; statistical pattern recognition method; Active shape model; Costs; Encoding; Face recognition; Feature extraction; Linear discriminant analysis; Neural networks; Random access memory; Read-write memory; Sun;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on

Conference_Location

Nanjing

Print_ISBN

0-7803-7702-8

Type

conf

DOI

10.1109/ICNNSP.2003.1279249

Filename

1279249