Bastien Durix, Géraldine Morin, S. Chambon, J. Mari, Kathryn Leonard
{"title":"One-step Compact Skeletonization","authors":"Bastien Durix, Géraldine Morin, S. Chambon, J. Mari, Kathryn Leonard","doi":"10.2312/egs.20191005","DOIUrl":null,"url":null,"abstract":"Computing a skeleton for a discretized boundary typically produces a noisy output, with a skeletal branch produced for each boundary pixel. A simplification step often follows to reduce these noisy branches. As a result, generating a clean skeleton is usually a 2-step process. In this article, we propose a skeletonization process that produces a clean skeleton in the first step, avoiding the creation of branches due to noise. The resulting skeleton compares favorably with the most common pruning methods on a large database of shapes. Our process also reduces execution time and requires only one parameter, e, that designates the desired boundary precision in the Hausdorff distance.","PeriodicalId":72958,"journal":{"name":"Eurographics ... Workshop on 3D Object Retrieval : EG 3DOR. Eurographics Workshop on 3D Object Retrieval","volume":"39 1","pages":"21-24"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics ... Workshop on 3D Object Retrieval : EG 3DOR. Eurographics Workshop on 3D Object Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/egs.20191005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Computing a skeleton for a discretized boundary typically produces a noisy output, with a skeletal branch produced for each boundary pixel. A simplification step often follows to reduce these noisy branches. As a result, generating a clean skeleton is usually a 2-step process. In this article, we propose a skeletonization process that produces a clean skeleton in the first step, avoiding the creation of branches due to noise. The resulting skeleton compares favorably with the most common pruning methods on a large database of shapes. Our process also reduces execution time and requires only one parameter, e, that designates the desired boundary precision in the Hausdorff distance.