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Summary: FUSION OF VISIBLE AND INFRARED IMAGES USING EMPIRICAL MODE
DECOMPOSITION TO IMPROVE FACE RECOGNITION
Harishwaran Hariharan, Andreas Koschan, Besma Abidi, Andrei Gribok
, and Mongi Abidi
Imaging, Robotics and Intelligent Systems Laboratory
ECE Department,
Nuclear Engineering Department
University of Tennessee, Knoxville, TN-37996
ABSTRACT
In this effort, we propose a new image fusion technique,
utilizing Empirical Mode Decomposition (EMD), for
improved face recognition. EMD is a non-parametric data-
driven analysis tool that decomposes non-linear non-
stationary signals into Intrinsic Mode Functions (IMFs). In
this method, we decompose images from different imaging
modalities into their IMFs. Fusion is performed at the
decomposition level and the fused IMFs are reconstructed to
form the fused image. The effect of fusion on face
recognition is measured by obtaining the Cumulative Match
Characteristics (CMCs) between galleries and probes. Apart
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