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Global Journal of Computer Science and Technology

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Global Journal of Computer Science and Technology
Graphics & Vision

Volume 13 Issue 4 Version 1.0 Year 2013
Type: Double Blind Peer Reviewed International Research Journal
Publisher: Global Journals Inc. (USA)
Online ISSN: 0975-4172 & Print ISSN: 0975-4350

Face Recognition using Local Binary Patterns (LBP)
By Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid
& Md. Shafiul Azam
Pabna University of Science and Technology, Bangladesh
Abstract - The face of a human being conveys a lot of information about identity and emotional state of the
person. Face recognition is an interesting and challenging problem, and impacts important applications in
many areas such as identification for law enforcement, authentication for banking and security system access,
and personal identification among others. In our research work mainly consists of three parts, namely face
representation, feature extraction and classification. Face representation represents how to model a face and
determines the successive algorithms of detection and recognition. The most useful and unique features of the
face image are extracted in the feature extraction phase. In the classification the face image is compared with
the images from the database. In our research work, we empirically evaluate face recognition which considers
both shape and texture information to represent face images based on Local Binary Patterns for personindependent face recognition. The face area is first divided into small regions from which Local Binary Patterns
(LBP), histograms are extracted and concatenated into a single feature vector. This feature vector forms an
efficient representation of the face and is used to measure similarities between images.
Keywords : local binary pattern (LBP), feature extraction, classification, pattern recognitin, histogram, feature
vector.
GJCST-F Classification: I.4.8

Face Recognition using Local Binary Patterns LBP
Strictly as per the compliance and regulations of:

© 2013. Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid & Md. Shafiul Azam. This is a research/review paper, distributed
under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License ), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited.

Face Recognition using Local Binary Patterns
(LBP)
information about identity and emotional state of the person.
Face recognition is a...
Global Journal of Computer Science and Technology
Graphics & Vision
Volume 13 Issue 4 Version 1.0 Year 2013
Type: Double Blind Peer Reviewed International Research Journal
Publisher: Global Journals Inc. (USA)
Online ISSN: 0975-4172 & Print ISSN: 0975-4350
Face Recognition using Local Binary Patterns (LBP)
Pabna University of Science and Technology, Bangladesh
Abstract -
The face of a human being conveys a lot of information about identity and emotional state of the
person. Face recognition is an interesting and challenging problem, and impacts important applications in
many areas such as identification for law enforcement, authentication for banking and security system access,
and personal identification among others. In our research work mainly consists of three parts, namely face
representation, feature extraction and classification. Face representation represents how to model a face and
determines the successive algorithms of detection and recognition. The most useful and unique features of the
face image are extracted in the feature extraction phase. In the classification the face image is compared with
the images from the database. In our research work, we empirically evaluate face recognition which considers
both shape and texture information to represent face images based on Local Binary Patterns for person-
independent face recognition. The face area is first divided into small regions from which Local Binary Patterns
(LBP), histograms are extracted and concatenated into a single feature vector. This feature vector forms an
efficient representation of the face and is used to measure similarities between images.
Keywords : local binary pattern (LBP), feature extraction, classification, pattern recognitin, histogram, feature
vector.
GJCST-F Classification: I.4.8
Face Recognition using Local Binary Patterns LBP
Strictly as per the compliance and regulations of:
© 2013. Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid & Md. Shafiul Azam. This is a research/review paper, distributed
under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creativecommons.org/licenses/by-
nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited.
By Md. Abdur Rahim, Md. Najmul Hossain, Tanzillah Wahid
& Md. Shafiul Azam
Global Journal of Computer Science and Technology - Trang 2
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