Abstract: For face recognition with single training sample per person，the conventional face recognition methods which work with many training samples don’t function well.Especially，a number of methods based on Fisher linear discriminant criterion can’t work because the within-class scatter matrix is a matrix with all elements being zero.To overcome the above problem，a new sample augment method is proposed in this paper.It slices the image at eight different planes（bit-planes）.It augments new training samples by combining the bit-planes images.Two-dimensional maximum scatter-difference discriminant analysis is performed on the new training images obtained.The experimental results on ORL face database show that the proposed method is effective and promising in face recognition with single training sample per person.