The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
IEEE Transactions on Pattern Analysis and Machine Intelligence
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Face Recognition with Relative Difference Space and SVM
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
An image preprocessing algorithm for illumination invariant face recognition
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Face recognition has been applied in many fields, while face recognition under uneven illumination is still an open problem. Our approach is based on Morphological Quotient Image (MQI) for illumination normalization, and Dynamic Morphological Quotient Image (DMQI) is proposed to improve the performance. Before applying MQI, singularity noise should be removed, and after MQI operation, an effective scheme is used to wipe off the grainy noise as postprocessing. Weighted normalized correlation is adopted to measure the similarity between two images. Experiments on Yale Face Database B show that the proposed MQI method has a good performance of face recognition under various light conditions. Moreover, its computational cost is very low.