Design of Face Recognition Algorithm Using Hybrid Data Preprocessing and Polynomial-Based RBF Neural Networks

  • Sung-Hoon Yoo
  • Sung-Kwun Oh
  • Kisung Seo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)


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.


Polynomial-based Radial Basis Function Neural Networks Principal Component Analysis Linear Discriminant Analysis Differential Evolution 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sung-Hoon Yoo
    • 1
  • Sung-Kwun Oh
    • 1
  • Kisung Seo
    • 2
  1. 1.Department of Electrical EngineeringThe University of SuwonGyeonggi-doSouth Korea
  2. 2.Department of Electronic EngineeringSeokyeong UniversitySeoulSouth Korea

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