Invariant recognition to position, rotation and scaleconsidering vectorial signatures

摘要

This work presents the development and utilization of vectorial signatures filters obtained from the application ofproperties of the scale and Fourier transform for images recognition. The filters were applied to different input scene,which consisted in the 26 letters of the alphabet. Each letter is an image of 256 X 256 pixels of black background with acentered white Arial letter. The image was rotated 360 degrees in increment of 1° and scaled from 70% to 130% inincrement of 0.5%. In order to find a new invariant correlation digital system we obtained two unidimensional vectorafter to achieve different mathematical transformation in the target as well as the input scene. To recognize a target,signatures were compared, calculating the Euclidean distance between the target and the input scene; then, confidencelevels are obtained. The results demonstrate that this system has a good performance to discriminate between letters.