一个用于骨架化的体素化植物根系数据的同源简化包

IF 0.4 4区 计算机科学 Q4 MATHEMATICS
Erin W. Chambers , Tao Ju , David Letscher , Hannah Schreiber , Dan Zeng
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引用次数: 0

摘要

在这项工作中,我们提出了VHS(体素化同调简化),这是一个c++包,其目的是去噪体素化数据并输出拓扑精确的简化形状。与之前在体素化同构简化工具上的工作相比,我们的主要目标是为计算形状分析的曲线骨架提供一个更好的起点。这个目标需要在其他包提供的基础上进行额外的简化,尽管我们的方法扩展并改进了先前在启发式方法上的工作,启发式方法计算同调简化问题的近似解。我们的工具是为体素化的植物根系设计和测试的,尽管它可能比这个数据集更有用。虽然一般来说,同调简化问题是np困难的,但当用于植物根系数据时,我们的包能够简化几乎所有的拓扑噪声。与现有的简化工具相比,我们的方法在拓扑简单性和几何精度之间取得了更好的平衡,从而提高了生成骨架的可用性。我们的代码可以在https://github.com/davidletscher/VHS/上公开获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VHS: A package for homological simplification of voxelized plant root data for skeletonization
In this work, we present VHS (Voxelized Homological Simplification), a C++ package whose purpose is to de-noise voxelized data and output a topologically accurate simplified shape. In contrast to previous work on voxelized homological simplification tools, our main goal is offering a better starting point for computing curve skeletons for shape analysis. This goal necessitates additional simplification beyond what other packages provide, although our approach extends and improves prior work on heuristic methods which compute approximate solutions for the homological simplification problem. Our tool is designed for and tested on voxelized plant roots, although it is potentially useful beyond this data set. While the homological simplification problem is NP-hard in general, our package is able to simplify almost all of the topological noise when used on data from plant root systems. Compared with existing simplification tools, our method strikes a better balance between topological simplicity and geometric accuracy, resulting in higher usability of the resulting skeletons. Our code is publicly available at https://github.com/davidletscher/VHS/.
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
43
审稿时长
>12 weeks
期刊介绍: Computational Geometry is a forum for research in theoretical and applied aspects of computational geometry. The journal publishes fundamental research in all areas of the subject, as well as disseminating information on the applications, techniques, and use of computational geometry. Computational Geometry publishes articles on the design and analysis of geometric algorithms. All aspects of computational geometry are covered, including the numerical, graph theoretical and combinatorial aspects. Also welcomed are computational geometry solutions to fundamental problems arising in computer graphics, pattern recognition, robotics, image processing, CAD-CAM, VLSI design and geographical information systems. Computational Geometry features a special section containing open problems and concise reports on implementations of computational geometry tools.
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