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Peeling the longest: A simple generalized curve reconstruction algorithm

机译:最长的剥离:一种简单的广义曲线重构算法

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摘要

Given a planar point set sampled from a curve, the curve reconstruction problem computes a polygonal approximation of the curve. In this paper, we propose a Delaunay triangulation-based algorithm for curve reconstruction, which removes the longest edge of each triangle to result in a graph. Further, each vertex of the graph is checked for a degree constraint to compute simple closed/open curves. Assuming ϵ-sampling, we provide theoretical guarantee which ensures that a simple closed/open curve is a piecewise linear approximation of the original curve. Input point sets with outliers are handled as part of the algorithm, without pre-processing. We also propose strategies to identify the presence of noise and simplify a noisy point set, identify self-intersections and enhance our algorithm to reconstruct such point sets. Perhaps, this is the first algorithm to identify the presence of noise in a point set. Our algorithm is able to detect closed/open curves, disconnected components, multiple holes and sharp corners. The algorithm is simple to implement, independent of the type of input, non-feature specific and hence it is a generalized one. We have performed extensive comparative studies to demonstrate that our method is comparable or better than other existing methods. Limitations of our approach have also been discussed.
机译:给定从曲线采样的平面点集,曲线重构问题将计算曲线的多边形近似值。在本文中,我们提出了一种基于Delaunay三角剖分的曲线重构算法,该算法去除了每个三角形的最长边以生成图形。此外,检查图形的每个顶点是否具有度约束,以计算简单的闭合/打开曲线。假设进行ϵ采样,我们提供了理论上的保证,可确保简单的闭合/打开曲线是原始曲线的分段线性逼近。具有离群值的输入点集将作为算法的一部分进行处理,而无需进行预处理。我们还提出了识别噪声的存在并简化噪声点集,识别自相交点并增强我们的算法以重建此类点集的策略。也许,这是第一种识别点集中是否存在噪声的算法。我们的算法能够检测闭合/打开的曲线,断开的零部件,多个孔和尖角。该算法易于实现,与输入类型无关,是非功能特定的,因此是一种通用算法。我们进行了广泛的比较研究,以证明我们的方法与其他现有方法具有可比性或更好。还讨论了我们方法的局限性。

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