Face recognition based on nonlinear DCT discriminant feature extraction using improved kernel DCV

Sheng Li, Yong Fang Yao, Xiao Yuan Jing, Heng Chang, Shi Qiang Gao, Dapeng Zhang, Jing Yu Yang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

8 Citations (Scopus)

Abstract

This letter proposes a nonlinear DCT discriminant feature extraction approach for face recognition. The proposed approach first selects appropriate DCT frequency bands according to their levels of nonlinear discrimination. Then, this approach extracts nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. the improved kernel discriminative common vector (KDCV) method. Experiments on the public FERET database show that this new approach is more effective than several related methods.
Original languageEnglish
Pages (from-to)2527-2530
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE92-D
Issue number12
DOIs
Publication statusPublished - 1 Jan 2009

Keywords

  • DCT frequency bands selection
  • Face recognition
  • Nonlinear DCT feature extraction
  • The improved KDCV

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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