Abstract: A reference pattern vector is obtained from training patterns belonging to each class and is held as a parameter of an original distance function in a distance dictionary. A discriminant function is defined which has, as variables, the difference between respective corresponding components of a feature vector of each training pattern and the corresponding reference pattern vector and the square of the difference. Training patterns of all classes are discriminated with the original distance function and a rival pattern set, which includes patterns misclassified as belonging to a respective class, is derived from the results of discrimination of the training patterns. A discriminant analysis is made between the training pattern set of each class and the corresponding rival pattern set to thereby determine parameters of the discriminant function, which are held in a discriminant dictionary.