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Face Recognition Using A Radial Basis Function Classifier
- Source :
- Proceedings 40th Annual 2006 International Carnahan Conference on Security Technology.
- Publication Year :
- 2006
- Publisher :
- IEEE, 2006.
-
Abstract
- Face recognition is probably the most natural way to perform a biometric authentication between human beings. However, the available technology for automatic systems still presents some drawbacks and is far away from human performance. In this paper we use the same DCT feature extraction approach presented in previous ICCST'03 and ICCST'05. However, we improve the experimental results using a Radial Basis Function (RBF) neural network in combination with the coding of the recognized class. We explain why the RBF, do not have the limitations of other classifiers such as the MLP. We also propose a method for dealing with the high number of classes associated to the task of face recognition which takes into account the limitations of the RBF as classifiers, and discuss the weakness of these methods when the number of training samples is limited. We have performed an exhaustive study about the neural network architecture and parameters, which has let us to establish relevant conclusions about the optimal configuration.
- Subjects :
- Artificial neural network
Biometrics
Computer science
business.industry
Feature extraction
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
Machine learning
computer.software_genre
Facial recognition system
ComputingMethodologies_PATTERNRECOGNITION
Discrete cosine transform
Radial basis function
Artificial intelligence
business
Classifier (UML)
computer
Coding (social sciences)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings 40th Annual 2006 International Carnahan Conference on Security Technology
- Accession number :
- edsair.doi...........f12b540f417e068e6dfaaf22d98b4758