NDLI: Best wavelet function for face recognition using multi-level decomposition

Content Provider	IEEE Xplore Digital Library
Author	Dawoud, N.N. Samir, B.B.
Copyright Year	2011
Description	Author affiliation: Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, Tronoh, Perak, Malaysia (Samir, B.B.) \|\| Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Perak, Malaysia (Dawoud, N.N.)
Abstract	The selection of appropriate wavelets is an important target for any application. In this paper, wavelets functions are examined in order to choose the best wavelet for face classification process and for finding the optimal number of levels of decomposition. Seven wavelet functions namely Symelt, Daubechig, Coiflets, Mayer Discrete, Biorthogonal, Reverse Biorthogonal and Haar were tested with different number of decomposition levels and different number of biggest coefficients is selected to reduce the huge feature dimension, and then the Euclidean Distance Method (EDM) was used for classification process. Also a statistical method has been proposed to produce new metric of features coefficients, the experiments brought about 40% improvements in comparison to the method that accounts the biggest coefficients from the four levels of decompositions. The experiments have been performed on Olivetti Research Laboratory database (ORL) and Yale University database (YALE). The result showed the effect of wavelets proprieties on classification process and the Symelt wavelets are the optimum wavelets for the face classification with four levels.
Starting Page	1
Ending Page	6
File Size	357852
Page Count	6
File Format	PDF
ISBN	9781612842950
e-ISBN	9781612842943
DOI	10.1109/ICRIIS.2011.6125749
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-23
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Euclidean distance method Databases Wavelet transform Feature extraction Wavelet analysis Discrete wavelet transforms Face Multi-level decomposing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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