{"title":"二维周期质心Voronoi镶嵌计算","authors":"Dong‐Ming Yan, K. Wang, B. Lévy, Laurent Alonso","doi":"10.1109/ISVD.2011.31","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an efficient algorithm to compute the centroidal Voronoi tessellation in 2D periodic space. We first present a simple algorithm for constructing the periodic Voronoi diagram (PVD) from a Euclidean Voronoi diagram. The presented PVD algorithm considers only a small set of periodic copies of the input sites, which is more efficient than previous approaches requiring full copies of the sites (9 in 2D and 27 in 3D). The presented PVD algorithm is applied in a fast Newton-based framework for computing the centroidal Voronoi tessellation (CVT). We observe that full-hexagonal patterns can be obtained via periodic CVT optimization attributed to the convergence of the Newton-based CVT computation.","PeriodicalId":152151,"journal":{"name":"2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"Computing 2D Periodic Centroidal Voronoi Tessellation\",\"authors\":\"Dong‐Ming Yan, K. Wang, B. Lévy, Laurent Alonso\",\"doi\":\"10.1109/ISVD.2011.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an efficient algorithm to compute the centroidal Voronoi tessellation in 2D periodic space. We first present a simple algorithm for constructing the periodic Voronoi diagram (PVD) from a Euclidean Voronoi diagram. The presented PVD algorithm considers only a small set of periodic copies of the input sites, which is more efficient than previous approaches requiring full copies of the sites (9 in 2D and 27 in 3D). The presented PVD algorithm is applied in a fast Newton-based framework for computing the centroidal Voronoi tessellation (CVT). We observe that full-hexagonal patterns can be obtained via periodic CVT optimization attributed to the convergence of the Newton-based CVT computation.\",\"PeriodicalId\":152151,\"journal\":{\"name\":\"2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISVD.2011.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Eighth International Symposium on Voronoi Diagrams in Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISVD.2011.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose an efficient algorithm to compute the centroidal Voronoi tessellation in 2D periodic space. We first present a simple algorithm for constructing the periodic Voronoi diagram (PVD) from a Euclidean Voronoi diagram. The presented PVD algorithm considers only a small set of periodic copies of the input sites, which is more efficient than previous approaches requiring full copies of the sites (9 in 2D and 27 in 3D). The presented PVD algorithm is applied in a fast Newton-based framework for computing the centroidal Voronoi tessellation (CVT). We observe that full-hexagonal patterns can be obtained via periodic CVT optimization attributed to the convergence of the Newton-based CVT computation.