NDLI: 1DLBP and PCA for face recognition

Content Provider	IEEE Xplore Digital Library
Author	Benzaoui, A. Boukrouche, A.
Copyright Year	2013
Description	Author affiliation: Dept. of Electron. & Telecommun., Univ. of 08 Mai 1945, Guelma, Algeria (Benzaoui, A.; Boukrouche, A.)
Abstract	A new algorithm for face recognition is proposed in this work, this algorithm is mainly based on LBP texture analysis in one dimensional space 1DLBP and Principal Component Analysis PCA as a technique for dimensionalities reduction. The extraction of the face's features is inspired from the principal that the human visual system combines between local and global features to differentiate between people. Starting from this assumption, the facial image is decomposed into several blocks with different resolution, and each decomposed block is projected in one dimensional space. Next, the proposed descriptor 1DLBP is applied for each projected block. Then, the resulting vectors will be concatenated in one global vector. Finley, Principal Component Analysis is used to reduce the dimensionalities of the global vectors and to keep only the pertinent information for each person. The experimental results applied on AR database have showed that the proposed descriptor 1DLBP combined with PCA have given a very significant improvement at the recognition rate and the false alarm rate compared with other methods of face recognition, and a good effectiveness against to deferent external factors as: illumination, rotations and noise.
Sponsorship	IEEE Algeria Subsect.
Starting Page	7
Ending Page	11
File Size	727237
Page Count	5
File Format	PDF
ISBN	9781479911523
e-ISBN	9781479911530
DOI	10.1109/ISPS.2013.6581486
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-04-22
Publisher Place	Algeria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Local binary pattern in one dimensional space (1DLBP) Dimesionalities reduction Principal Compenent Analysis (PCA) Texture description Databases Face recognition Lighting Local binary pattern (LBP) Feature extraction Vectors Face Principal component analysis
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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