Face Recognition by Regularized-LDA Using PRM

Author

Dora, Lingraj ; Rath, N.P.

Author_Institution

Electr. & Telecomm. Eng. Dept., V.S.S.U.T, ODISHA, Sambalpur, India

fYear

2010

fDate

16-17 Oct. 2010

Firstpage

140

Lastpage

145

Abstract

Face recognition has received an increased attention from several years in the field of image analysis, pattern recognition, and computer vision. In this paper we propose a method to the problem of face recognition. The proposed method consists of two stages. In the first stage regularized linear discriminant analysis is used to extract the most significant and discriminant features and then in the second stage, these features are used by probabilistic reasoning model for classification of unknown face images. Here two databases, the ORL database and the UMIST database are used for experiments and to show the performance of the proposed method.

Keywords

face recognition; feature extraction; image classification; inference mechanisms; visual databases; ORL database; PRM; UMIST database; face recognition; feature extraction; probabilistic reasoning model; regularized linear discriminant analysis; regularized-LDA; unknown face image clasification; Databases; Eigenvalues and eigenfunctions; Face; Feature extraction; Principal component analysis; Testing; Training; Eigenface; Face recognition; Fisherface; Regularized-LDA (R-LDA); linear discriminant analysis (LDA); probabilistic reasoning model (PRM);

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Recent Technologies in Communication and Computing (ARTCom), 2010 International Conference on

Conference_Location

Kottayam

Print_ISBN

978-1-4244-8093-7

Electronic_ISBN

978-0-7695-4201-0

Type

conf

DOI

10.1109/ARTCom.2010.50

Filename

5656921