A novel pattern classification algorithm called Affine subspace Nearest Points (ASNP) algorithm is presented in this paper. Inspired by the geometrical explanation of Support Vector Machine (SVM) and the nearest point method

in which the optimal separating plane bisects the closest points within two convex hulls

the ASNP algorithm expands the searching areas of the closest points from the convex hulls to their corresponding class affine subspaces. The affine subspaces are taken as the rough estimations of the class sample distributions

and their closest points are found. Then

the hyperplane to separate the affine subspaces with the maximal margins is constructed

which is the perpendicular bisector of the line segment joining the two closest points. The test experiments compared with the Nearest Neighbor (1 NN) classifier and SVM on the ORL face recognition database showed good performance of this algorithm.