NDLI: Face recognition using Local Quaternion Patters and Weighted Spatially constrained Earth Mover's Distance

Content Provider	IEEE Xplore Digital Library
Author	Wei Zhou Ahrary, A. Kamata, S.-i.
Copyright Year	2009
Description	Author affiliation: Graduate School of Information, Production and System, Waseda University, Kitakyushu, Japan (Wei Zhou; Kamata, S.-i.) \|\| Information, Production and System Research Center, Waseda University, Kitakyushu, Japan (Ahrary, A.)
Abstract	This paper presents a novel algorithm for face recognition. Local Quaternion Patters (LQP) is proposed for presenting the feature parts in the face. To keep the spatial feature of the face, an asymmetric similarity measure Weighted Spatially constrained Earth Mover's Distance (WSEMD) is studied for classification. In this step, the source image is partitioned into non overlapping local patches while the destination image is represented as a set of overlapping local patches at different positions and Gaussian Kernel is used. Finally, local and global weighting is applied to get a more accurate classifier. To evaluate the proposed method and its performance, three well-known and challenge face databases - ORL, Yale and FERET are used in our study. The experimental results show that the proposed method has higher accuracy than some other classic methods.
Starting Page	285
Ending Page	289
File Size	697948
Page Count	5
File Format	PDF
ISBN	9781424429752
DOI	10.1109/ISCE.2009.5156971
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-25
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face recognition Quaternions Earth Production systems Spatial databases Image databases Feature extraction Consumer electronics Partitioning algorithms Weight measurement WSEMD Local Quaternion Patterns (LQP) face recognition feature extraction
Content Type	Text
Resource Type	Article

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