区域增长欧氏距离变换的应用:各向异性和骨架

Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing Pub Date : 1997-10-26 DOI:10.1109/ICIP.1997.647446

O. Cuisenaire, B. Macq

{"title":"区域增长欧氏距离变换的应用:各向异性和骨架","authors":"O. Cuisenaire, B. Macq","doi":"10.1109/ICIP.1997.647446","DOIUrl":null,"url":null,"abstract":"A new region growing algorithm has been proposed for computing Euclidean distance maps in a time comparable to widely used chamfer distance transform. We show how this algorithm can be extended to more complex tasks such as the computation of distance maps on anisotropic grids and the generation of a new type of Euclidean skeletons.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"14 1","pages":"200-203 vol.1"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Applications of the region growing Euclidean distance transform: anisotropy and skeletons\",\"authors\":\"O. Cuisenaire, B. Macq\",\"doi\":\"10.1109/ICIP.1997.647446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new region growing algorithm has been proposed for computing Euclidean distance maps in a time comparable to widely used chamfer distance transform. We show how this algorithm can be extended to more complex tasks such as the computation of distance maps on anisotropic grids and the generation of a new type of Euclidean skeletons.\",\"PeriodicalId\":92344,\"journal\":{\"name\":\"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing\",\"volume\":\"14 1\",\"pages\":\"200-203 vol.1\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.1997.647446\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.1997.647446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 18

摘要

提出了一种新的区域增长算法，在相当长的时间内计算欧几里得距离图，与广泛使用的倒角距离变换相当。我们展示了如何将该算法扩展到更复杂的任务，例如各向异性网格上距离图的计算和新型欧几里得骨架的生成。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Applications of the region growing Euclidean distance transform: anisotropy and skeletons

A new region growing algorithm has been proposed for computing Euclidean distance maps in a time comparable to widely used chamfer distance transform. We show how this algorithm can be extended to more complex tasks such as the computation of distance maps on anisotropic grids and the generation of a new type of Euclidean skeletons.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing

自引率

0.00%

发文量