Invariant correlation to position and rotation using a binary mask applied to binary and gray images

Abstract

In this paper more alternative ways to generate the binary ring masks are studied and a new methodology is presented when in the analysis the image come with some distortion due to rotation. This new algorithm requires low computational cost. Signature vectors of the target so like signature vectors of the object to be recognized in the problem image are obtained using a binary ring mask constructed in accordance with the real or the imaginary part of their Fourier transform analyzing two different conditions in each one. In this manner, each image target or problem image, will have four unique binary ring masks. The four ways are analyzed and the best is chosen. In addition, due to any image with rotation include some distortion, the best transect is chosen in the Fourier plane in order to obtain the best signature through the different ways to obtain the binary mask. This methodology is applied to two cases: to identify different types of alphabetic letters in Arial font and to identify different fossil diatoms images. Considering the great similarity between diatom images the results obtained are excellent.