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A neural network based human identification framework using ear images

Alaraj, Maen, Hou, Jingyu and Fukami, Tadanori 2010, A neural network based human identification framework using ear images, in TENCON 2010 : Proceedings of the 2010 IEEE Region 10 Conference, IEEE, Piscataway, N.J., pp. 1595-1600.

Document type: Conference Paper
Collection: School of Information Technology
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Title A neural network based human identification framework using ear images
Author(s) Alaraj, Maen
Hou, Jingyu
Fukami, Tadanori
Conference name IEEE Region 10 Conference (2010 : Fukuoka, Japan)
Conference location Fukuoka, Japan
Conference dates 21-24 Nov. 2010
Title of proceedings TENCON 2010 : Proceedings of the 2010 IEEE Region 10 Conference
Editor(s) [Unknown]
Publication date 2010
Conference series IEEE Region 10 Conference
Start page 1595
End page 1600
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) human identification
principal component analysis
neural network
ear image
pattern recognition
Summary 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.
ISBN 9781424468881
9781424468904
Language eng
Field of Research 080106 Image Processing
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category E1 Full written paper - refereed
HERDC collection year 2010
Copyright notice ©2010, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30033763
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