Erin W. Chambers , Tao Ju , David Letscher , Hannah Schreiber , Dan Zeng
{"title":"一个用于骨架化的体素化植物根系数据的同源简化包","authors":"Erin W. Chambers , Tao Ju , David Letscher , Hannah Schreiber , Dan Zeng","doi":"10.1016/j.comgeo.2025.102198","DOIUrl":null,"url":null,"abstract":"<div><div>In this work, we present VHS (<strong>V</strong>oxelized <strong>H</strong>omological <strong>S</strong>implification), 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 <span><span>https://github.com/davidletscher/VHS/</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":51001,"journal":{"name":"Computational Geometry-Theory and Applications","volume":"130 ","pages":"Article 102198"},"PeriodicalIF":0.4000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"VHS: A package for homological simplification of voxelized plant root data for skeletonization\",\"authors\":\"Erin W. Chambers , Tao Ju , David Letscher , Hannah Schreiber , Dan Zeng\",\"doi\":\"10.1016/j.comgeo.2025.102198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this work, we present VHS (<strong>V</strong>oxelized <strong>H</strong>omological <strong>S</strong>implification), 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 <span><span>https://github.com/davidletscher/VHS/</span><svg><path></path></svg></span>.</div></div>\",\"PeriodicalId\":51001,\"journal\":{\"name\":\"Computational Geometry-Theory and Applications\",\"volume\":\"130 \",\"pages\":\"Article 102198\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Geometry-Theory and Applications\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0925772125000367\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Geometry-Theory and Applications","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0925772125000367","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS","Score":null,"Total":0}
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/.
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.