Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70177
Title: Face recognition using multi-feature and radial basis function network
Authors: Su, HT
Feng, D
Zhao, RC
Keywords: Face recognition
Classification
Radius base function network
Principal component analysis
Linear discriminant analysis
Frequency domain
Fourier frequency spectrum
Issue Date: 2003
Publisher: Australian Computer Society
Source: Conferences in research and practice in information technology, May 2003, v. 22, p. 51-57 How to cite?
Journal: Conferences in research and practice in information technology 
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.
Description: 2002 Pan-Sydney Workshop on Visualisation (VIP'2002), Sydney, Australia, 2002
URI: http://hdl.handle.net/10397/70177
ISBN: 1-920682-01-5
ISSN: 1445-1336
Appears in Collections:Conference Paper

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