Performance Evaluation of Infrared and Visible Image Fusion Algorithms for Face Recognition

DOI

10.2991/iske.2007.234How to use a DOI?

Keywords

Image fusion, Performance evaluation, Face recognition, Singular value decomposition

Abstract

Fusion of infrared and visible image is a potential solution to improve face recognition performance. In this paper, we propose a new fusion method based on singular value decomposition (SVD) and apply it to multiple spectrum face recognition. The performance of the proposed SVD-based fusion method is compared with that of average fusion, Laplacian Pyramid Decomposition (LPD) based fusion and Discrete Wavelet Transform (DWT) based fusion methods. The performances of the four image fusion methods for face recognition are analyzed by statistical experiments and the results show that the SVD-based fusion method is better in most conditions.

Copyright

© 2007, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Wang
AU  - Jimin Liang
AU  - Haihong Hu
AU  - Yan Li
PY  - 2007/10
DA  - 2007/10
TI  - Performance Evaluation of Infrared and Visible Image Fusion Algorithms for Face Recognition
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 1379
EP  - 1386
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.234
DO  - 10.2991/iske.2007.234
ID  - Wang2007/10
ER  -