Modelling of face recognitions systems using mnemonic description of the model

Abstract

This paper belongs to area of automatic face recognition systems for biometrics tasks. And it represents a new way of modeling with the use of mnemonic description of the model in face recognition systems. This way of modeling allows more quickly, precisely and simply to create face recognition system for experiments. In addition mnemonic description allows to exchange results of work more precisely. And it also promotes faster training and carrying out experiments as doesn’t demand studying of additional programming languages. Mnemonic description can be useful as to the beginning researchers, experts and also employees from related fields of knowledge. The results of modeling of the most known face recognition system are presented in the work, such as: 1DPCA, 2DPCA and Fisherfaces (LDA) with the public bases use of persons images: «AT & T-ORL», «The Extended Yale Face Database B» and «The Yale Database A».