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15 September 2008 Invariant recognition to position, rotation, and scale considering vectorial signatures
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Abstract
This work presents the development and utilization of vectorial signatures filters obtained from the application of properties 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 × 256 pixels of black background with a centered white Arial letter. The image was rotated 360 degrees in increment of 1o and scaled from 70% to 130% in increment of 0.5%. In order to find a new invariant correlation digital system we obtained two unidimensional vector after 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, confidence levels are obtained. The results demonstrate that this system has a good performance to discriminate between letters.
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Jesús R. Lerma A., Josué Álvarez-Borrego, and José Ángel González-Fraga "Invariant recognition to position, rotation, and scale considering vectorial signatures", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707329 (15 September 2008); https://doi.org/10.1117/12.795301
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