A parallel, O(N) algorithm for unbiased, thin watershed

T. Chabardès, P. Dokládal, M. Faessel, M. Bilodeau
{"title":"A parallel, O(N) algorithm for unbiased, thin watershed","authors":"T. Chabardès, P. Dokládal, M. Faessel, M. Bilodeau","doi":"10.1109/ICIP.2016.7532823","DOIUrl":null,"url":null,"abstract":"The watershed transform is a powerful tool for morphological segmentation. Most common implementations of this method involve a strict hierarchy on gray tones in processing the pixels composing an image. Those dependencies complexify the efficient use of modern computational architectures. This paper aims at answering this problem by introducing a new way of simulating the waterflood that alleviates the sequential nature of hierachical queue propagation. Simultaneous and disorderly growth is made possible using this method. higher speed is reached and bigger data volume can be processed. Experimental results show that the algorithm is accurate and produces a thin, well centered watershed line.","PeriodicalId":6521,"journal":{"name":"2016 IEEE International Conference on Image Processing (ICIP)","volume":"357 1","pages":"2569-2573"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2016.7532823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

The watershed transform is a powerful tool for morphological segmentation. Most common implementations of this method involve a strict hierarchy on gray tones in processing the pixels composing an image. Those dependencies complexify the efficient use of modern computational architectures. This paper aims at answering this problem by introducing a new way of simulating the waterflood that alleviates the sequential nature of hierachical queue propagation. Simultaneous and disorderly growth is made possible using this method. higher speed is reached and bigger data volume can be processed. Experimental results show that the algorithm is accurate and produces a thin, well centered watershed line.
一个并行,O(N)算法的无偏,薄分水岭
分水岭变换是形态学分割的有力工具。该方法的大多数常见实现涉及在处理构成图像的像素时对灰度色调进行严格的层次结构。这些依赖关系使现代计算体系结构的有效使用变得复杂。本文旨在通过引入一种新的模拟水驱的方法来解决这一问题,该方法减轻了分层队列传播的顺序性。用这种方法可以使同时无序生长成为可能。达到更高的速度,可以处理更大的数据量。实验结果表明,该算法具有较高的精度,并能生成一条细而圆心良好的分水岭线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信