@inbook{08bd8e8563d44e37b9326a55432b8183,
title = "A novel feature vectors construction approach for face recognition",
abstract = "This paper discusses a novel feature vectors construction approach for face recognition using discrete wavelet transform (DWT). Pour 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.",
keywords = "Face recognition, discrete wavelet transform, coefficient selection, feature selection, feature optimization",
author = "Paul Nicholl and Afandi Ahmad and Abbes Amira",
year = "2010",
doi = "10.1007/978-3-642-17697-5_12",
language = "English",
isbn = "9783642176968",
series = "Lecture Notes in Computer Science",
publisher = "Springer-Verlag Berlin",
pages = "223--248",
editor = "Gavrilova, {Marina L.} and Tan, {C.J. Kenneth} and Moreno, {Edward David}",
booktitle = "Transactions on Computational Science XI",
}