Orthogonalized Fisher discriminant

The Foley–Sammon discriminant (FSD) exhibits higher performance in face recognition than the Fisher linear discriminant due to its elimination of dependences among discriminant vectors. But its theory is complex and the calculation is time expensive. The orthogonalized Fisher discriminant (OFD), whi...

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Bibliographic Details
Published inPattern recognition Vol. 38; no. 2; pp. 311 - 313
Main Authors Song, Fengxi, Liu, Shuhai, Yang, Jingyu
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.02.2005
Subjects
Face recognition
Linear discriminant
Nearest neighbor classifier
Orthogonal set of vectors
Pattern classification
Orthogonal set of vectors
Face recognition
Pattern classification
Linear discriminant
Nearest neighbor classifier
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Summary:The Foley–Sammon discriminant (FSD) exhibits higher performance in face recognition than the Fisher linear discriminant due to its elimination of dependences among discriminant vectors. But its theory is complex and the calculation is time expensive. The orthogonalized Fisher discriminant (OFD), which also derives a set of orthogonal discriminant vectors, is very simple and easy to implement. Experiments show that OFD is more effective and efficient than FSD in pattern recognition.
ISSN:0031-3203
1873-5142
DOI:10.1016/j.patcog.2004.06.007