Post-processed LDA for face and palmprint recognition: What is the rationale

Wangmeng Zuo, Hongzhi Zhang, Dapeng Zhang, Kuanquan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

25 Citations (Scopus)


Linear discriminant analysis (LDA)-based methods have been very successful in face and palmprint recognition. Recently, a class of post-processing approaches has been proposed to improve the recognition performance of LDA in face recognition. In-depth analysis, however, has not been presented to reveal the effectiveness of the post-processing approach. In this paper, we first investigate the rationale of the post-processing approach using a Gaussian function, and demonstrate the mutual relationship between the post-processing approach and the image Euclidean distance (IMED) method. We further extend the post-processing approach to palmprint recognition and use the FERET face and the PolyU palmprint databases to evaluate the post-processed LDA method. Experimental results indicate that the post-processing approach is effective in improving the recognition rate for LDA-based face and palmprint recognition.
Original languageEnglish
Pages (from-to)2344-2352
Number of pages9
JournalSignal Processing
Issue number8
Publication statusPublished - 1 Aug 2010


  • Dimensionality reduction
  • Face recognition
  • Feature extraction
  • Linear discriminant analysis (LDA)
  • Palmprint recognition

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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