Face recognition using DCT and hierarchical RBF model

Authors:
Yuehui Chen;Yaou Zhao
Affiliations:
School of Information Science and Engineering, Jinan University, Jinan, P.R. China;School of Information Science and Engineering, Jinan University, Jinan, P.R. China
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

Citing 6
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Abstract

This paper proposes a new face recognition approach by using the Discrete Cosine Transform (DCT) and Hierarchical Radial Basis Function Network (HRBF) classification model. The DCT is employed to extract the input features to build a face recognition system, and the HRBF is used to identify the faces. Based on the pre-defined instruction/operator sets, a HRBF model can be created and evolved. This framework allows input features selection. The HRBF structure is developed using Extended Compact Genetic Programming (ECGP) and the parameters are optimized by Differential Evolution (DE). Empirical results indicate that the proposed framework is efficient for face recognition.