In order to apply the manifold learning approach to image dimension reduction and recognition

an affine invariant adaptive locally linear embedding algorithm is proposed. Tangent distance is introduced and combined with locally linear embedding. In the sample space

the distance is described by an affine invariant image similarity based on the tangent distance method. The neighborhood size of every point in sample space is computed adaptively by simi-larity function. Experimental results show that the proposed algorithm is able to create low dimensional manifold structure more reasonably

and improve the recognition rate. The proposed algorithm is insensitive to affine transformation and performs more robust.