Affine-invariant correlation of gray-scale characters using GAT iteration

Introduces a new technique of affine-invariant correlation of gray-scale characters by reinforcing correlation-based matching in two ways. The first method is the use of normalized cross-correlation as a matching measure based on definite canonicalization in order to realize robustness against image degradation. The second method is the application of an iterative global affine transformation (GAT) to the input image, so as to realize the maximal affine-invariant correlation with the target image. The advantages and effectiveness of the proposed method are both shown theoretically and demonstrated through preliminary experiments using gray-scale images of numerals subject to a wide range of affine transformations and random Gaussian noise.