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A novel illumination normalization algorithm for face recognition

Face recognitions systems suffer from the problem associated with illumination variation. Therefore, there's a need to address this problem. In this paper, we present a novel algorithm for illumination normalization call Local Trapezoid Feature LTF. The features are derived from the trapezoid rule and the experiments results on extended Yale face database demonstrated the effectiveness and the superiority of the algorithm. Furthermore, our algorithm doesn't require dimensionality reduction or feature extraction.