Face recognition based on discriminant waveletfaces

Limin Cui, Yuan Yan Tang, Fucheng Liao, Xiufeng Du

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

2 Citations (Scopus)

Abstract

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been widely applied in the face detection and recognition, yet still they have some limitations such as poor discriminative power and large computational load. This paper presents a method for face recognition using discriminant waveletfaces. Firstly wavelet transform is used to decompose the face image into different frequency subbands for extracting feature - waveletfaces, and then the discriminant analysis of PCA plus LDA is performed on the chosen subband. Finally the nearest neighbor classifier is adopted to make decision. In comparison with the traditional discriminant analysis, the experiments show that the proposed approach has better recognition rate and can reduce the computational load.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
PublisherIEEE
Pages3561-3565
Number of pages5
ISBN (Electronic)9781424409914
ISBN (Print)1424409918, 9781424409907
DOIs
Publication statusPublished - 7 Oct 2007
Event2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
Duration: 7 Oct 200710 Oct 2007

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
PublisherIEEE
ISSN (Print)1062-922X

Conference

Conference2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Country/TerritoryCanada
CityMontreal, QC
Period7/10/0710/10/07

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