Discrete geometric estimators aim at estimating geometric characteristics of a shape with only its digitization as input data. Such an estimator is multigrid convergent when its estimates tend toward the geometric characteristics of the shape as the digitization step h tends toward 0. This paper studies the multigrid convergence of tangent estimators based on maximal digital straight segment recognition. We show that such estimators are multigrid convergent for some family of convex shapes and that their speed of convergence is on average Ο(h2/3). Experiments confirm this result and suggest that the bound is tight. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Lachaud, J. O., & De Vieilleville, F. (2006). Convex shapes and convergence speed of discrete tangent estimators. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4292 LNCS-II, pp. 688–697). Springer Verlag. https://doi.org/10.1007/11919629_69
Mendeley helps you to discover research relevant for your work.