Face recognition using multi-feature and radial basis function network

Authors:
Su Hongtao;David Dagan Feng;Zhao Rong-chun
Affiliations:
Center of Multimedia Signal processing, Dept. of EIE, Hong Kong Polytechnic University, Hong Kong and Dept. of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China;Center of Multimedia Signal processing, Dept. of EIE, Hong Kong Polytechnic University, Hong Kong and School of Information Technologies, University of Sydney, Australia;Dept. of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China
Venue:
VIP '02 Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22
Year:
2003

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Abstract

In this paper, a face recognition algorithm using multi feature and Radial basis Function Network (RBFN) is proposed. The algorithm consists of three steps. In the first step, a coarse classification is performed using Fourier frequency spectrum feature, and only the first k gallery images with minimum Euclidean distance to the probe image are retained. In the second step, the Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) features of frequency spectrum are extracted, which will be taken as the input of the RBFN in the third step. In the last step, the classification is carried out by using RBFN. The proposed approach has been tested on ORL face database and Shimon database. The experimental results have demonstrated that the performance of this algorithm is much superior to the other algorithms on the same database.