Invariant correlation to position, rotation, and scale using one-dimensional composite filters

A nonlinear correlation digital algorithm invariant to position, rotation and scale using a binary mask is presented. In order to analyze this new identification digital system binary and gray images are used. The problem images had a ±30% of maximum scale variation with respect to the target. Some composite filters had a very good performance in this range. The rotation goes from 0° to 359°. Concentric binary rings masks were elaborated, from the Fourier transform, using the real or the imaginary part. The signatures of the problem image and the target were obtained from the ring mask. The objective is identifying a specific target no matter the position, rotation or scale presented in the problem image. A statistical analysis was done to know the mean correlation confidence level. In this work, a new, fast and functional position, scale and rotation invariance pattern recognition digital system was obtained.