Orthogonalized Fisher discriminant

摘要

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.