Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Interpretation and Coding of Face Images Using Flexible Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust image based 3d face recognition
Robust image based 3d face 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
The CMU Pose, Illumination, and Expression Database
IEEE Transactions on Pattern Analysis and Machine Intelligence
Total Variation Models for Variable Lighting Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
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Face detection and recognition technologies have a wide range of applications, while varying illumination typically make these technologies perform poorly. The illumination variations heavily affect the effectiveness of face visualization and face recognition. The novelty in this paper is that quadratic polynomial model is applied to illumination compensation. Experimental results demonstrate that the proposed algorithm performs well not only in weakening illumination effect but also in improving the face recognition rates. From the experiments, we can find that face recognition rate can reach 99.17%, and the visualization effectiveness of images is greatly improved.