Title :
Two-parameter Fisher criterion
Author_Institution :
Fac. of Electron. Telecommun. & Inf., Tech. Univ. Gdansk, Poland
fDate :
8/1/2001 12:00:00 AM
Abstract :
This paper proposes further generalization of a multiclass Fisher´s criterion. A formula describing the dependence between the generalized multiclass Fisher´s criterion FΘ and the variance criterion FvΘ has been obtained. Using this formula, it has been shown that the feature extraction methods based on the Karhunen-Loeve (K-L) expansions are special cases of the discriminant method. A full evaluation of heuristic methods for feature extraction based on the K-L expansion with regard to discriminant methods has been presented. A new algorithm for sequential feature extraction has been proposed and is illustrated with an example
Keywords :
Karhunen-Loeve transforms; feature extraction; image classification; Karhunen-Loeve expansions; discriminant method; discriminant methods; feature extraction methods; heuristic methods; two-parameter Fisher criterion; variance criterion; Classification tree analysis; Design methodology; Feature extraction; Gaussian distribution; Informatics; Mean square error methods; Neural networks; Pattern classification; Pattern recognition; Scattering;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.938265