Digital system of invariant correlation to position and rotation

Abstract

A new correlation digital system invariant to position and rotation is presented. This new algorithm requires low computational cost, because it uses uni-dimensional signatures (vectors). The signature of the target so like the signature of the object to be recognized in the problem image is obtained using a binary ring mask constructed based on the real positive values of the Fourier transform of the corresponding image. In this manner, each image will have one unique binary ring mask, avoiding in this form the relevant information leak. Using linear and non-linear correlations, this methodology is applied first in the identification of the alphabet letters in Arial font style and then in the classification of fossil diatoms images. Also, this system is tested using the diatom images with additive Gaussian noise. The non-linear correlation results were excellent, obtaining in this way a simple but efficient method to achieve rotation and translation invariance pattern recognition.