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Proceedings Paper

Pattern recognition descriptor using the Z-Fisher transform
Author(s): Carolina Barajas-García; Selene Solorza-Calderón; Josué Álvarez-Borrego
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Paper Abstract

In this work is presented a pattern recognition image descriptor invariant to rotation, scale and translation (RST), which classify images using the Z-Fisher transform. A binary rings mask is generated using the Fourier transform. The normalized analytic Fourier-Mellin amplitude spectrum is filtered with that mask to build 1D signature. The signatures comparison of the problem image and the target are done by the Pearson correlation coefficient (PCC). In general, those PCC values do not satisfy a normal distribution, hence the Fisher’s Z distribution is employed to determine the confidence level of the RST invariant descriptor. The descriptor presents a confidence level of 95%.

Paper Details

Date Published: 22 September 2015
PDF: 8 pages
Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 95992M (22 September 2015); doi: 10.1117/12.2188616
Show Author Affiliations
Carolina Barajas-García, Univ. Autónoma de Baja California (Mexico)
Selene Solorza-Calderón, Univ. Autónoma de Baja California (Mexico)
Josué Álvarez-Borrego, Ctr. de Investigación Científica y de Educación Superior de Ensenada (Mexico)

Published in SPIE Proceedings Vol. 9599:
Applications of Digital Image Processing XXXVIII
Andrew G. Tescher, Editor(s)

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