Face recognition based on a novel linear discriminant criterion

Fengxi Song, Dapeng Zhang, Qinglong Chen, Jizhong Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)


As an effective technique for feature extraction and pattern classification Fisher linear discriminant (FLD) has been successfully applied in many fields. However, for a task with very high-dimensional data such as face images, conventional FLD technique encounters a fundamental difficulty caused by singular within-class scatter matrix. To avoid the trouble, many improvements on the feature extraction aspect of FLD have been proposed. In contrast, studies on the pattern classification aspect of FLD are quiet few. In this paper, we will focus our attention on the possible improvement on the pattern classification aspect of FLD by presenting a novel linear discriminant criterion called maximum scatter difference (MSD). Theoretical analysis demonstrates that MSD criterion is a generalization of Fisher discriminant criterion, and is the asymptotic form of discriminant criterion: large margin linear projection. The performance of MSD classifier is tested in face recognition. Experiments performed on the ORL, Yale, FERET and AR databases show that MSD classifier can compete with top-performance linear classifiers such as linear support vector machines, and is better than or equivalent to combinations of well known facial feature extraction methods, such as eigenfaces, Fisherfaces, orthogonal complementary space, nullspace, direct linear discriminant analysis, and the nearest neighbor classifier.
Original languageEnglish
Pages (from-to)165-174
Number of pages10
JournalPattern Analysis and Applications
Issue number3
Publication statusPublished - 1 Aug 2007


  • Binary linear classifier
  • Face recognition
  • Fisher linear discriminant
  • Multi-objective programming
  • Pattern classification
  • Small sample size problem

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


Dive into the research topics of 'Face recognition based on a novel linear discriminant criterion'. Together they form a unique fingerprint.

Cite this