Title :
Multiscale fusion of visual and thermal images for robust face recognition
Author :
Kwon, Oh-Kyu ; Kong, Seong G.
Author_Institution :
Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN
fDate :
March 31 2005-April 1 2005
Abstract :
This paper presents data fusion of visual and thermal infrared (IR) images in discrete wavelet transform (DWT) domain for robust face recognition. A combined use of face images in visible and thermal IR spectra has demonstrated robustness in face recognition under illumination variations. In the proposed approach, different fusion rules are applied separately to the approximation and the details components of the level-2 DWT decomposition to produce illumination-invariant face images. In case eyeglasses are present in the face, thermal images fail to provide useful information around the eyes since glass blocks a large portion of thermal energy. The DWT-based fusion method preserves visual details of eyeglass regions useful for face recognition in the fused images. Experiment results demonstrate that the fusion method is effective in terms of both visual quality and the entropy compared to conventional fusion approaches
Keywords :
discrete wavelet transforms; face recognition; infrared imaging; infrared spectra; sensor fusion; IR spectra; data fusion; discrete wavelet transform; illumination-invariant face images; multiscale visual-thermal infrared images fusion; robust face recognition; thermal energy; Discrete wavelet transforms; Entropy; Eyes; Face recognition; Glass; Infrared imaging; Infrared spectra; Lighting; Robustness; Wavelet domain;
Conference_Titel :
Computational Intelligence for Homeland Security and Personal Safety, 2005. CIHSPS 2005. Proceedings of the 2005 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9176-4
DOI :
10.1109/CIHSPS.2005.1500623