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Boundary fitting for 2D curve reconstruction

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Abstract

In this paper we present a 3-step algorithm for reconstructing curves from unorganized points: data clustering to filter out the noise, data confining to get the boundary, and region thinning to find the skeleton curve. The method is effective in removing far-from-the-shape noise and in handling a shape of changing density. The algorithm takes O(nlog n) time and O(n) space for a set of n points.

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Authors and Affiliations

  1. Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, P.O. Box 2704-28, Beijing, 100190, China

    Yuqing Song

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  1. Yuqing Song
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Correspondence to Yuqing Song.

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Song, Y. Boundary fitting for 2D curve reconstruction. Vis Comput 26, 187–204 (2010). https://doi.org/10.1007/s00371-009-0395-4

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  • DOI: https://doi.org/10.1007/s00371-009-0395-4

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