首页> 外文会议>Advances in Visual Computing pt.2; Lecture Notes in Computer Science; 4292 >Convex Shapes and Convergence Speed of Discrete Tangent Estimators
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Convex Shapes and Convergence Speed of Discrete Tangent Estimators

机译:离散正切估计的凸形状和收敛速度

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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 O(h~(3/2)). Experiments confirm this result and suggest that the bound is tight.
机译:离散几何估计器旨在仅以数字化为输入数据来估计形状的几何特征。当数字化步长h趋于0时,这种估计量趋于形状的几何特征时,该估计量便是多网格收敛的。本文基于最大数字直线段识别研究切线估计量的多网格收敛。我们证明了这种估计量对于某些凸形族是多重网格收敛的,并且它们的收敛速度平均为O(h〜(3/2))。实验证实了这一结果,并表明边界是紧密的。

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