Face recognition based on discriminant fractional Fourier feature extraction

Xiao Yuan Jing, Hau San Wong, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

32 Citations (Scopus)

Abstract

Developed from the conventional Fourier transform, the fractional Fourier transform is a powerful signal analysis and processing technique. In this paper, we apply it to the field of face recognition. By combining it with the discrimination analysis technique, we propose a new face recognition approach. First, we use a two-dimensional separability judgment to select appropriate value of angle parameter for discrete fractional Fourier transform. Second, we present a reformative Fisherface method to extract discriminative features from the preprocessed images and perform the classification using the nearest neighbor classifier. Experimental results on two public face databases indicate that our approach outperforms four representative discrimination methods. It obtains better and robust classification effects.
Original languageEnglish
Pages (from-to)1465-1471
Number of pages7
JournalPattern Recognition Letters
Volume27
Issue number13
DOIs
Publication statusPublished - 1 Oct 2006

Keywords

  • Angle parameter
  • Face recognition
  • Feature extraction
  • Fractional Fourier transform
  • Linear discrimination analysis
  • Reformative Fisherface method

ASJC Scopus subject areas

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

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