Estimation of moments of digitized objects with fuzzy borders

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Abstract

Error bounds for estimation of moments from a fuzzy representation of a shape are derived, and compared with estimations from a crisp representation, It is shown that a fuzzy membership function based on the pixel area coverage provides higher accuracy of the estimates, compared to binary Gauss digitization at the same spatial image resolution. Theoretical results are confirmed by a statistical study of disks and squares, where the moments of the shape, up to order two, are estimated from its fuzzy discrete representation. The errors of the estimates decrease both with increased size of a shape (spatial resolution) and increased membership resolution (number of available grey-levels). © Springer-Verlag Berlin Heidelberg 2005.

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Sladoje, N., & Lindblad, J. (2005). Estimation of moments of digitized objects with fuzzy borders. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 188–195). https://doi.org/10.1007/11553595_23

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