A Fourier-LDA approach for image recognition

Xiao Yuan Jing, Yuan Yan Tang, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

49 Citations (Scopus)

Abstract

Fourier transform and linear discrimination analysis (LDA) are two commonly used techniques of image processing and recognition. Based on them, we propose a Fourier-LDA approach (FLA) for image recognition. It selects appropriate Fourier frequency bands with favorable linear separability by using a two-dimensional separability judgment. Then it extracts two-dimensional linear discriminative features to perform the classification. Our experimental results on different image data prove that FLA obtains better classification performance than other linear discrimination methods.
Original languageEnglish
Pages (from-to)453-457
Number of pages5
JournalPattern Recognition
Volume38
Issue number3
DOIs
Publication statusPublished - 1 Mar 2005

Keywords

  • Fourier transform
  • Fourier-LDA approach (FLA)
  • Frequency-band selection
  • Linear discrimination analysis (LDA)
  • Two-dimensional separability judgment

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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