Near infrared face recognition based on wavelet transform and 2DPCA

Yuqing He*, Guangqin Feng, Feihu Liu, Huan He

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

A feature extraction algorithm of near-infrared human face based on wavelet transform and 2DPCA (two-dimension principal component analysis) was proposed. This algorithm firstly applied wavelet transform to the near-infrared face images, obtained the low frequency components of face images, and removed high frequency components. Secondly applied 2DPCA to the low frequency components of the face images for feature extraction. Finally completed the face recognition using Euclidean distance .The experimental results based on near-infrared face database clearly showed that the proposed algorithm could get higher recognition rate than the traditional PCA and 2DPCA algorithm, which demonstrated the efficiency of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 2010 International Conference on Intelligent Computing and Integrated Systems, ICISS2010
Pages359-362
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 IEEE International Conference on Intelligent Computing and Integrated Systems, ICISS2010 - Guilin, China
Duration: 22 Oct 201024 Oct 2010

Publication series

NameProceedings - 2010 International Conference on Intelligent Computing and Integrated Systems, ICISS2010

Conference

Conference2010 IEEE International Conference on Intelligent Computing and Integrated Systems, ICISS2010
Country/TerritoryChina
CityGuilin
Period22/10/1024/10/10

Keywords

  • 2DPCA
  • Biometrics
  • Face recognition
  • Near-infrared
  • Wavelet transform

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