A face and palmprint recognition approach based on discriminant DCT feature extraction

Xiao Yuan Jing, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

193 Citations (Scopus)


In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.
Original languageEnglish
Pages (from-to)2405-2415
Number of pages11
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Issue number6
Publication statusPublished - 1 Dec 2004


  • DCT frequency band selection
  • Discrete cosine transform (DCT)
  • Improved Fisherface method
  • Linear discrimination technique
  • Two-dimensional (2-D) separability judgment

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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