A lyapunov theory-based neural network approach for face recognition
This chapter presents a new face recognition system comprising of feature extraction and the Lyapunov theory-based neural network. It first gives the definition of face recognition which can be broadly divided into (i) feature-based approaches, and (ii) holistic approaches. A general review of both...
| Main Authors: | , , , |
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| Format: | Book Chapter |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/20.500.11937/2710 |
| _version_ | 1848744027902443520 |
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| author | Ang, L. Lim, Hann Seng, K. Chin, S. |
| author_facet | Ang, L. Lim, Hann Seng, K. Chin, S. |
| author_sort | Ang, L. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This chapter presents a new face recognition system comprising of feature extraction and the Lyapunov theory-based neural network. It first gives the definition of face recognition which can be broadly divided into (i) feature-based approaches, and (ii) holistic approaches. A general review of both approaches will be given in the chapter. Face features extraction techniques including Principal Component Analysis (PCA) and Fisher's Linear Discriminant (FLD) are discussed. Multilayered neural network (MLNN) and Radial Basis Function neural network (RBF NN) will be reviewed. Two Lyapunov theory-based neural classifiers: (i) Lyapunov theory-based RBF NN, and (ii) Lyapunov theory-based MLNN classifiers are designed based on the Lyapunov stability theory. The design details will be discussed in the chapter. Experiments are performed on two benchmark databases, ORL and Yale. Comparisons with some of the existing conventional techniques are given. Simulation results have shown good performance for face recognition using the Lyapunov theory-based neural network systems. © 2010, IGI Global. |
| first_indexed | 2025-11-14T05:54:56Z |
| format | Book Chapter |
| id | curtin-20.500.11937-2710 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T05:54:56Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-27102017-09-13T14:30:53Z A lyapunov theory-based neural network approach for face recognition Ang, L. Lim, Hann Seng, K. Chin, S. This chapter presents a new face recognition system comprising of feature extraction and the Lyapunov theory-based neural network. It first gives the definition of face recognition which can be broadly divided into (i) feature-based approaches, and (ii) holistic approaches. A general review of both approaches will be given in the chapter. Face features extraction techniques including Principal Component Analysis (PCA) and Fisher's Linear Discriminant (FLD) are discussed. Multilayered neural network (MLNN) and Radial Basis Function neural network (RBF NN) will be reviewed. Two Lyapunov theory-based neural classifiers: (i) Lyapunov theory-based RBF NN, and (ii) Lyapunov theory-based MLNN classifiers are designed based on the Lyapunov stability theory. The design details will be discussed in the chapter. Experiments are performed on two benchmark databases, ORL and Yale. Comparisons with some of the existing conventional techniques are given. Simulation results have shown good performance for face recognition using the Lyapunov theory-based neural network systems. © 2010, IGI Global. 2009 Book Chapter http://hdl.handle.net/20.500.11937/2710 10.4018/978-1-60566-798-0.ch002 restricted |
| spellingShingle | Ang, L. Lim, Hann Seng, K. Chin, S. A lyapunov theory-based neural network approach for face recognition |
| title | A lyapunov theory-based neural network approach for face recognition |
| title_full | A lyapunov theory-based neural network approach for face recognition |
| title_fullStr | A lyapunov theory-based neural network approach for face recognition |
| title_full_unstemmed | A lyapunov theory-based neural network approach for face recognition |
| title_short | A lyapunov theory-based neural network approach for face recognition |
| title_sort | lyapunov theory-based neural network approach for face recognition |
| url | http://hdl.handle.net/20.500.11937/2710 |