Shape analysis for object recognition using number theoretic transforms

A method of shape recognition involving fast correlation techniques based on number theoretic transforms (NTTs) is outlined. NTTs facilitate the computation of convolutions with no roundoff error and are ideally suited for implementation on current bit-serial word-parallel machines such as the DAP-500. The transforms can be carried out by a combination of shifts and adds with all arithmetic performed modulo some integer number. They produce very fast implementations at the price of limiting the input to integer values over a finite field. In the present application the pixel values describing an object boundary are in precisely this form so that the advantages of the NTT can be obtained at no cost in quantization or clipping noise. Results of correlating shapes which have undergone various transformations are presented