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Proceedings Paper

Infrared face recognition using texture descriptors
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Paper Abstract

Face recognition is an area of computer vision that has attracted a lot of interest from the research community. A growing demand for robust face recognition software in security applications has driven the development of interesting approaches in this field. A large quantity of research in face recognition deals with visible face images. In the visible spectrum the illumination and face expressions changes represent a significant challenge for the recognition system. To avoid these problems, researchers proposed recently the use of 3D and infrared imaging for face recognition. In this work, we introduce a new framework for infrared face recognition using texture descriptors. This framework exploits linear and non linear dimensionality reduction techniques for face learning and recognition in the texture space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. Two multispectral face recognition databases were used in our experiments: Equinox Database (Visible, SWIR, MWIR, LWIR) and Laval University Multispectral Database (Visible, NIR, MWIR, LWIR). The obtained results show high increase in recognition performance when texture descriptors like LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) are used. The best result was obtained in the short wave infrared spectrum (SWIR) using non linear dimensionality reduction techniques.

Paper Details

Date Published: 4 May 2010
PDF: 10 pages
Proc. SPIE 7661, Thermosense XXXII, 766109 (4 May 2010); doi: 10.1117/12.849764
Show Author Affiliations
Moulay A. Akhloufi, Univ. Laval (Canada)
Abdelhakim Bendada, Univ. Laval (Canada)

Published in SPIE Proceedings Vol. 7661:
Thermosense XXXII
Ralph B. Dinwiddie; Morteza Safai, Editor(s)

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