In this paper a rotation, scale and translation (RST) invariant pattern recognition digital system based on 1D signatures is proposed. The rotation invariance is obtained using the Radon transform, the scale invariance is achieved by the analytical Fourier-Mellin transform and the translation invariance is realized through the Fourier’s amplitude spectrum of the image. Once, the RST invariant Radon- Fourier-Mellin (RFM) image is generated (a 2D RST invariant), the marginal frequencies of that image are used to build a RST invariant 1D signature. The Latin alphabet letters in Arial font style were used to test the system. According with the statistical method of bootstrap the pattern recognition system yields a confidence level at least of 95%.
CITATION STYLE
Solorza-Calderón, S., & Verdugo-Olachea, J. (2015). A RFM pattern recognition system invariant to rotation, scale and translation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9423, pp. 477–484). Springer Verlag. https://doi.org/10.1007/978-3-319-25751-8_57
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