International Journal of applied mathematics and computer science

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Paper details

Number 1 - March 2020
Volume 30 - 2020

Curve skeleton extraction via k-nearest-neighbors based contraction

Jianling Zhou, Ji Liu, Min Zhang

We propose a skeletonization algorithm that is based on an iterative points contraction. We make an observation that the local center that is obtained via optimizing the sum of the distance to k nearest neighbors possesses good properties of robustness to noise and incomplete data. Based on such an observation, we devise a skeletonization algorithm that mainly consists of two stages: points contraction and skeleton nodes connection. Extensive experiments show that our method can work on raw scans of real-world objects and exhibits better robustness than the previous results in terms of extracting topology-preserving curve skeletons.

curve skeleton, points contraction, point cloud, k nearest neighbors