Abstract-Face recognition is a popular application of pattern recognition methods, and it faces challenging problems including illumination, expression, and pose. The most popular way is to learn the subspaces of the face images so that it could be project to another discriminant space where images of different persons can be separated. In this paper, a nearest line projection algorithm is developed to represent the face images for face recognition. Instead of projecting an image to its nearest image, we try to project it to its nearest line spanned by two different face images. The subspaces are learned so that each face image to its nearest line is minimized. We evaluated the proposed algorithm on some benchmark face image database, and also compared it to some other image projection algorithms. The experiment results showed that the proposed algorithm outperforms other ones.
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