Rock image segmentation using watershed with shape markers

A. Amankwah, C. Aldrich
{"title":"Rock image segmentation using watershed with shape markers","authors":"A. Amankwah, C. Aldrich","doi":"10.1109/AIPR.2010.5759719","DOIUrl":null,"url":null,"abstract":"We propose a method for the creation of object markers used in watershed segmentation of rock images. First, we use adaptive thresholding to segment the rock image since rock particles local background is often different from surrounding particle regions. Object markers are then extracted using the compactness of objects and adaptive morphological reconstruction. The choice of the feature compactness is motivated by the fact that crushed rocks tend to have rounded shapes. Experimental results after comparing the segmented images show that the performance of our algorithm is superior to most standard methods of watershed segmentation. We also show that the proposed algorithm was more robust in the estimation of fines in rock samples than the traditional methods.","PeriodicalId":128378,"journal":{"name":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2010.5759719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

We propose a method for the creation of object markers used in watershed segmentation of rock images. First, we use adaptive thresholding to segment the rock image since rock particles local background is often different from surrounding particle regions. Object markers are then extracted using the compactness of objects and adaptive morphological reconstruction. The choice of the feature compactness is motivated by the fact that crushed rocks tend to have rounded shapes. Experimental results after comparing the segmented images show that the performance of our algorithm is superior to most standard methods of watershed segmentation. We also show that the proposed algorithm was more robust in the estimation of fines in rock samples than the traditional methods.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
带形状标记的分水岭岩石图像分割
我们提出了一种用于岩石图像分水岭分割的目标标记的创建方法。首先,由于岩石颗粒的局部背景通常与周围颗粒区域不同,我们采用自适应阈值分割方法对岩石图像进行分割。然后利用对象的紧密度和自适应形态重建提取对象标记。选择紧凑性的原因是碎石往往呈圆形。实验结果表明,该算法的分割性能优于大多数标准的分水岭分割方法。我们还表明,与传统方法相比,该算法在估计岩石样品中的细粒方面具有更强的鲁棒性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automated cross-sensor registration, orthorectification and geopositioning using LIDAR digital elevation models Gray-level co-occurrence matrices as features in edge enhanced images Rock image segmentation using watershed with shape markers Adaptive selection of visual and infra-red image fusion rules Tactical geospatial intelligence from full motion video
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1