Application of image correction and bit-plane fusion in generalized PCA based face recognition
Pattern Recognition Letters
Robust face recognition by combining projection-based image correction and decomposed eigenface
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Generalized PCA face recognition by image correction and bit feature fusion
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Real-time face tracking and recognition by sparse eigentracker with associative mapping to 3D shape
Image and Vision Computing
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Image correction is discussed for realizing both effective object recognition and realistic image-based rendering. Three image normalizations are compared in relation with the linear subspaces and eigenspaces, and we conclude that the normalization by L1-norm, which normalizes the total sum of Intensities, is the best for our purposes. Based on noise analysis in the normalized image space (NIS), an image correction algorithm is constructed, which is accomplished by iterative projections along with corrections of an image to an eigenspace in NIS. Experimental results show that the proposed method works well for natural images which include various kinds of noise shadows, reflections and occlusions. The proposed method provides a feasible solution to the object recognition based on the illumination cone [2]. The technique can also be extended to face detection of unknown person and registration/recognition using eigenfaces.