A statistical analysis of Fukunaga-Koontz transform

The Fukunaga-Koontz transform (FKT) has been proposed as a feature selection methodology for nearly 32 years. There are a huge number of citations. We have not seen a direct analysis between FKT, and a well established statistical method: Fisher quadratic discriminant analysis (QDA). In this letter,...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 11; no. 2; pp. 123 - 126
Main Author Huo, X.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2004
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Analysis of variance
Computer vision
Convolution
Covariance matrix
Discriminant analysis
Eigenvalues and eigenfunctions
Face detection
Joints
Linear discriminant analysis
Links
Methodology
Signal processing
Statistical analysis
Statistical distributions
Statistical methods
Target recognition
Transforms
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Summary:The Fukunaga-Koontz transform (FKT) has been proposed as a feature selection methodology for nearly 32 years. There are a huge number of citations. We have not seen a direct analysis between FKT, and a well established statistical method: Fisher quadratic discriminant analysis (QDA). In this letter, under certain assumptions, we establish such a connection. We speculate that a link in a more general situation is hard to find.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2003.821650