An optimal symmetrical null space criterion of Fisher discriminant for feature extraction and recognition

DOI10.1007/S00500-010-0682-ZzbMath1237.68175OpenAlexW2105081321MaRDI QIDQ422428

Xibei Yang, Xiaoning Song, Xiao-Jun Wu, Jing-Yu Yang

Publication date: 16 May 2012

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-010-0682-z

zbMATH Keywords

feature extractionsmall sample size problemFisher discriminant criterionsymmetrical null space

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (1)

A fuzzy supervised learning method with dynamical parameter estimation for nonlinear discriminant analysis

Uses Software

• KPCA plus LDA
• FERET
• ORL face

Cites Work

• Subspace evolution analysis for face representation and recognition
• A linear discriminant analysis framework based on random subspace for face recognition
• Linear dimensionality reduction by maximizing the Chernoff distance in the transformed space
• Feature extraction for one-class classification problems: Enhancements to biased discriminant analysis
• Bagging, boosting and the random subspace method for linear classifiers
• From image vector to matrix: A straightforward image projection technique -- IMPCA vs. PCA
• A direct LDA algorithm for high-dimensional data -- with application to face recognition

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