  Face recognition is a popular application of pat- tern 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.
