A. Cuadros-Vargas, L. G. Nonato, R. Minghim, Tiago Etiene
{"title":"Imesh: An Image Based Quality Mesh Generation Technique","authors":"A. Cuadros-Vargas, L. G. Nonato, R. Minghim, Tiago Etiene","doi":"10.1109/SIBGRAPI.2005.31","DOIUrl":null,"url":null,"abstract":"Generating triangular meshes from images is a task important to many applications. Usually, techniques that can do that either take as starting point a segmented image or generate a mesh without distinguishing different structures contained in the image. In both cases the results can be satisfactory for a number of applications, but the pre-segmentation and the absence of well defined structures imply in difficulties using the resulting mesh for simulations. Furthermore, guarantee of good quality meshes is also a common problem in previous results. In this work we present a new technique for mesh generation that handles these problems well. First, it eliminates the need for pre-processing by building the segmentation into the mesh generation process. Second, the mesh generation process takes into acount the quality of the mesh elements, producing as result meshes of better quality than previous techniques.","PeriodicalId":193103,"journal":{"name":"XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"XVIII Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIBGRAPI.2005.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Generating triangular meshes from images is a task important to many applications. Usually, techniques that can do that either take as starting point a segmented image or generate a mesh without distinguishing different structures contained in the image. In both cases the results can be satisfactory for a number of applications, but the pre-segmentation and the absence of well defined structures imply in difficulties using the resulting mesh for simulations. Furthermore, guarantee of good quality meshes is also a common problem in previous results. In this work we present a new technique for mesh generation that handles these problems well. First, it eliminates the need for pre-processing by building the segmentation into the mesh generation process. Second, the mesh generation process takes into acount the quality of the mesh elements, producing as result meshes of better quality than previous techniques.