Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Multisensor integration and fusion for intelligent machines and systems
Multisensor integration and fusion for intelligent machines and systems
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision Fusion
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Illumination Cones for Recognition under Variable Lighting: Faces
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Illumination Normalization for Robust Face Recognition Against Varying Lighting Conditions
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Face Recognition in Hyperspectral Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recent advances in visual and infrared face recognition: a review
Computer Vision and Image Understanding
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
An Indoor and Outdoor, Multimodal, Multispectral and Multi-Illuminant Database for Face Recognition
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Physics-based Fusion of Multispectral Data for Improved Face Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Face recognition from visible and near-infrared images using boosted directional binary code
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
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Novel image fusion approaches, including physics-based weighted fusion, illumination adjustment and rank-based decision level fusion, for spectral face images are proposed for improving face recognition performance compared to conventional images. A new multispectral imaging system is briefly presented which can acquire continuous spectral face images for our concept proof with fine spectral resolution in the visible spectrum. Several experiments are designed and validated by calculating the cumulative match characteristics of probe sets via the well-known recognition engine-FaceIt®. Experimental results demonstrate that proposed fusion methods outperform conventional images when gallery and probes are acquired under different illuminations and with different time lapses. In the case where probe images are acquired outdoors under different daylight situations, the fused images outperform conventional images by up to 78%.