Robust of Low Rank Matrix and Collaborative Representation for Face Recognition - Rokan Khaji Rusul Ismail Khalil (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
In this paper, we have introduced improvement Robustness method for face recognition, which combine of the low-rank with collaborative representation. The applications of this model are based on the truth that proposed method can effectively deal with the face recognition across different illumination and occlusion, as well as the nature of corrupted and occluded regions. The method is able to be applied directly on original face image neither does it require feature selection, nor does it need many training samples. Experiments have been performed on various benchmark face database. The proposed method outperforms many state-of-the-art methods.