Robustness in image recognition refers to the ability to perceive an image pattern regardless of factors including camera views and locations. This paper proposes an image normalization algorithm that allows an image with arbitrary projective distortions to be recognized efficiently. The normalization algorithm calculates the required projective transformation matrix using image moments. For an input image, a set of 8 output images that are independent of projective deformations are generated. The proposed algorithm is evaluated on three benchmark data sets. The experimental results show that the proposed normalization is significantly more accurate than the existing rank minimization and affine normalization methods.