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A novel feature vectors construction approach for face recognition

Nicholl, Paul and Ahmad , Afandi and Amira, Abbes (2010) A novel feature vectors construction approach for face recognition. In: Transactions on Computational Science XI. Lecture Notes in Computer Science, 6480 . Springer-Verlag Berlin Heidelberg, pp. 223-248. ISBN 978-3-642-17697-5 (Unpublished)

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This paper discusses a novel feature vectors construction approach for face recognition using discrete wavelet transform (DWT). Four experiments have been carried out focusing on: DWT feature selection, DWT filter choice, features optimization by coefficients selection as well as feature threshold. In order to explore the most suitable method of feature extraction, different wavelet quadrant and scales have been studied. It then followed with an evaluation of different wavelet filter choices and their impact on recognition accuracy. An approach for face recognition based on coefficient selection for DWT is the presented and analyzed. Moreover, a study has been deployed to investigate ways of selecting the DWT coefficient threshold. The results obtained using the AT&T database have shown a significant achievement over existing DWT/PCA coefficient selection techniques and the approach presented increases recognition accuracy from 94% to 97% when the Coiflet 3 wavelet is used.

Item Type: Book Section
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 21 Feb 2013 08:09
Last Modified: 21 Feb 2013 08:09
URI: http://eprints.uthm.edu.my/id/eprint/3051
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