A novel feature vectors construction approach for face recognition

Authors:
Paul Nicholl;Afandi Ahmad;Abbes Amira
Affiliations:
School of Electronics, Electrical Engineering and Computer Science, The Queens University, Belfast, Northern Ireland;Dept. of Electronic and Computer Eng., School of Eng. and Design, Brunel Univ., Uxbridge, United Kingdom and Department of Computer Eng., Faculty of Electrical and Electronic Eng., Universiti Tun ...;Nanotechnology and Integrated Bio-Engineering Centre, Faculty of Computing and Engineering, University of Ulster, Co Antrim, Northern Ireland
Venue:
Transactions on computational science XI
Year:
2010

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Abstract

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.