Abstract
This study introduces a design of face recognition algorithm based on hybrid data preprocessing and polynomial-based RBF neural network. The overall face recognition system consists of two parts such as the preprocessing part and recognition part. The proposed polynomial-based radial basis function neural networks is used as an the recognition part of overall face recognition system, while a hybrid algorithm developed by a combination of PCA and LDA is exploited to data preprocessing. The essential design parameters (including learning rate, momentum, fuzzification coefficient and feature selection) are optimized by means of the differential evolution (DE). A well-known dataset AT&T database is used to evaluate the performance of the proposed face recognition algorithm.
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© 2012 Springer-Verlag Berlin Heidelberg
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Yoo, SH., Oh, SK., Seo, K. (2012). Design of Face Recognition Algorithm Using Hybrid Data Preprocessing and Polynomial-Based RBF Neural Networks. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_24
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DOI: https://doi.org/10.1007/978-3-642-31362-2_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31361-5
Online ISBN: 978-3-642-31362-2
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