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Soft Computing
Erschienen in: Soft Computing 13/2019

09.04.2018 | Methodologies and Application

Design of face recognition system based on fuzzy transform and radial basis function neural networks

verfasst von: Seok-Beom Roh, Sung-Kwun Oh, Jin-Hee Yoon, Kisung Seo

Erschienen in: Soft Computing | Ausgabe 13/2019

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Abstract

In this study, a face recognition method based on fuzzy transform and radial basis function neural networks is proposed. In order to reduce the dimensionality and extract the important features of face images, fuzzy transform with fuzzy partition techniques is used. Fuzzy radial basis function neural networks (FRBFNNs) are used as a classifier to identify face images into several categories. Radial basis functions are defined by fuzzy C-means clustering method which can analyze the distribution of data points over the input spaces. In order to validate the proposed face recognition system, experimental comparative studies are conducted on the benchmark face datasets such as YALE, ORL, and ABERDEEN databases. A comparative analysis demonstrates that the proposed face recognition system is superior to the conventional face recognition techniques.
Vorheriger Artikel Gradient evolution-based counter propagation network for approximation of noncanonical system
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Metadaten
Titel
Design of face recognition system based on fuzzy transform and radial basis function neural networks
verfasst von
Seok-Beom Roh
Sung-Kwun Oh
Jin-Hee Yoon
Kisung Seo
Publikationsdatum
09.04.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 13/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3161-6

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