Abstract
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%.
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Van der Lugt, A.: Signal detection by complex spatial filtering. IEEE Trans. Inf. Theory IT–10, 139–145 (1964)
Vijaya Kumar, B.V.K., Hassebrook, L.: Performance measures for correlation filters. Appl. Opt. 29, 2997–3006 (1990)
Lowe, D.G.: Distinctive image features from scale-invariant key points. IJCV 60, 91–110 (2004)
Bay, H., Essa, A., Tuytelaars, T., Van Gool, L.: Speeded-Up Robust Features (SURF). CVIU 110, 346–359 (2008)
Lerma-Aragón, J.L., Álvarez-Borrego, J.: Vectorial signatures for invariant recognition of position, rotation and scale pattern recognition. J. Mod. Opt. 56, 1598–1606 (2009)
Solorza, S., Álvarez-Borrego, J.: Translation and rotation invariant pattern recognition by binary rings masks. J. Mod. Opt. 62, 851–864 (2015)
Solís-Ventura, A., Álvarez-Borrego, J., Solorza, S.: An adaptive nonlinear correlation with a binary mask invariant to rotation and scale applied to identify phytoplankton. Opt. Commun. 339, 185–193 (2015)
Hoang, T.V., Tabbone, S.: Invariant pattern recognition using the RFM descriptor. Pattern Recogn. 45, 271–284 (2012)
Derrode, S., Ghorbel, F.: Robust and efficient Fourier-Mellin transform approximations for gray-level image reconstruction and complete invariant description. CVIU 83, 57–78 (2001)
Ghorbel, F.: Towards a unitary formulation for invariant image description; Application to Towards a unitary formualtion for invariant image description. Application to image coding. Ann. Telecommun. 53, 242–260 (1998)
Davison, A.C., Hinkley, D.V.: Bootstrap methods and their application. Cambridge University Press, New York (1997)
Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital image processing using Matlab. Gatesmark Publishing, MA (2009)
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© 2015 Springer International Publishing Switzerland
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Solorza-Calderón, S., Verdugo-Olachea, J. (2015). A RFM Pattern Recognition System Invariant to Rotation, Scale and Translation. In: Pardo, A., Kittler, J. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2015. Lecture Notes in Computer Science(), vol 9423. Springer, Cham. https://doi.org/10.1007/978-3-319-25751-8_57
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DOI: https://doi.org/10.1007/978-3-319-25751-8_57
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