A neural network based human identification framework using ear images
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2010
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Resumo |
This paper presents a framework that uses ear images for human identification. The framework makes use of Principal Component Analysis (PCA) for ear image feature extraction and Multilayer Feed Forward Neural Network for classification. Framework are proposed to improve recognition accuracy of human identification. The framework was tested on an ear image database to evaluate its reliability and recognition accuracy. The experimental results showed that our framework achieved higher stable recognition accuracy and over-performed other existing methods. The recognition accuracy stability and computation time with respect to different image sizes and factors were investigated thoroughly as well in the experiments.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dro.deakin.edu.au/eserv/DU:30033763/hou-TENCON-evidence-2010.pdf http://dro.deakin.edu.au/eserv/DU:30033763/hou-TENCONacceptence-evidence-2010.pdf http://dro.deakin.edu.au/eserv/DU:30033763/hou-neuralnetworkbased-2010.pdf http://dx.doi.org/10.1109/TENCON.2010.5686043 |
Direitos |
2010, IEEE |
Palavras-Chave | #human identification #principal component analysis #neural network #ear image #pattern recognition |
Tipo |
Conference Paper |