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Face Description with Local Binary Patterns Application to Face Recognition
1Face Description with Local Binary Patterns:
Application to Face Recognition
Timo Ahonen, Student Member, IEEE, Abdenour Hadid,
and Matti Pietika?inen, Senior Member, IEEE
Abstract
This paper presents a novel and efficient facial image representation based on
local binary pattern (LBP) texture features. The face image is divided into several
regions from which the LBP feature distributions are extracted and concatenated into
an enhanced feature vector to be used as a face descriptor. The performance of the
proposed method is assessed in the face recognition problem under different challenges.
Other applications and several extensions are also discussed.
Index Terms
Facial image representation, local binary pattern, component-based face recogni-
tion, texture features, face misalignment
I. INTRODUCTION
Automatic face analysis which includes, e.g., face detection, face recognition and facial
expression recognition has become a very active topic in computer vision research [1]. A
key issue in face analysis is finding efficient descriptors for face appearance. Different holistic
methods such as Principal Component Analysis (PCA) [2], Linear Discriminant Analysis (LDA)
[3] and the more recent 2-D PCA [4] have been studied widely but lately also local descriptors
T. Ahonen, A. Hadid, and M. Pietika?inen are with the Machine Vision Group, Infotech Oulu, Department of Electrical and
Information Engineering, University of Oulu, PO Box 4500, FIN-90014, Finland. E-mail: ftahonen, hadid, mkpg@ee.oulu.fi.
5th June 2006 DRAFT
2have gained attention due to their robustness to challenges such as pose and illumination changes.
This paper presents a novel descriptor based on local binary pattern texture features extracted
from local facial regions.
One of the first face descriptors based on information extracted from local regions is the
eigenfeatures method proposed by Pentland et al. [5]. This is a hybrid approach in which
the features are obtained by performing PCA to local face
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