Abstract
This paper is addressing problems related to the construction of classifiers based on the Similarity Discriminant Function (SDF), in which the traditional vector representation of a pattern is replaced with matrix data. We introduce potential modifications of the matrix data structure and propose new variants of the SDF. The algorithms that we present were tested on images of handwritten digits and on photographs of human faces, taken from the ORL and CMU-PIE databases. The results of experiments show that our modifications significantly improved the performance of the original SDF classifier. © 2012 Wiley Periodicals, Inc.
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