Pattern matching based on a generalized Fourier transform

In a two-dimensional pattern matching problem, a known template image has be located in another image, irrespective of the template's position, orientation and size in the image. One way to accomplish invariance to the changes in the template is by forming a set of feature vectors that encompass all the variations in the template. Matching is then performed by finding the best similarity between the feature vector extracted from the image to the feature vectors in the template set. In this paper we introduce a new concept of a generalized Fourier transform. The generalized Fourier transform offers a relatively robust and extremely fast solution to the described matching problem. The application of the generalized Fourier transform to scale invariant pattern matching is shown here.