基于-分割算法的磨损颗粒图像分割

IF 1.5 Q3 ENGINEERING, MECHANICAL Advances in Tribology Pub Date : 2016-04-18 DOI:10.1155/2016/4931502
Hong Liu, Haijun Wei, Lidui Wei, Jing-ming Li, Zhiyuan Yang
{"title":"基于-分割算法的磨损颗粒图像分割","authors":"Hong Liu, Haijun Wei, Lidui Wei, Jing-ming Li, Zhiyuan Yang","doi":"10.1155/2016/4931502","DOIUrl":null,"url":null,"abstract":"This study aims to use a JSEG algorithm to segment the wear particle’s image. Wear particles provide detailed information about the wear processes taking place between mechanical components. Autosegmentation of their images is key to intelligent classification system. This study examined whether this algorithm can be used in particles’ image segmentation. Different scales have been tested. Compared with traditional thresholding along with edge detector, the JSEG algorithm showed promising result. It offers a relatively higher accuracy and can be used on color image instead of gray image with little computing complexity. A conclusion can be drawn that the JSEG method is suited for imaged wear particle segmentation and can be put into practical use in wear particle’s identification system.","PeriodicalId":44668,"journal":{"name":"Advances in Tribology","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2016-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/4931502","citationCount":"5","resultStr":"{\"title\":\"The Segmentation of Wear Particles Images Using -Segmentation Algorithm\",\"authors\":\"Hong Liu, Haijun Wei, Lidui Wei, Jing-ming Li, Zhiyuan Yang\",\"doi\":\"10.1155/2016/4931502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to use a JSEG algorithm to segment the wear particle’s image. Wear particles provide detailed information about the wear processes taking place between mechanical components. Autosegmentation of their images is key to intelligent classification system. This study examined whether this algorithm can be used in particles’ image segmentation. Different scales have been tested. Compared with traditional thresholding along with edge detector, the JSEG algorithm showed promising result. It offers a relatively higher accuracy and can be used on color image instead of gray image with little computing complexity. A conclusion can be drawn that the JSEG method is suited for imaged wear particle segmentation and can be put into practical use in wear particle’s identification system.\",\"PeriodicalId\":44668,\"journal\":{\"name\":\"Advances in Tribology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2016-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2016/4931502\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Tribology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2016/4931502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Tribology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2016/4931502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 5

摘要

本研究旨在利用JSEG算法对磨损颗粒图像进行分割。磨损颗粒提供了机械部件之间发生磨损过程的详细信息。图像的自动分割是智能分类系统的关键。本研究考察了该算法能否用于粒子图像分割。已经测试了不同的尺度。与传统的阈值分割和边缘检测器相比较,JSEG算法取得了较好的效果。它提供了相对较高的精度,可用于彩色图像代替灰度图像,计算复杂度低。结果表明,JSEG方法适合于图像磨损颗粒的分割,可在磨损颗粒识别系统中实际应用。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The Segmentation of Wear Particles Images Using -Segmentation Algorithm
This study aims to use a JSEG algorithm to segment the wear particle’s image. Wear particles provide detailed information about the wear processes taking place between mechanical components. Autosegmentation of their images is key to intelligent classification system. This study examined whether this algorithm can be used in particles’ image segmentation. Different scales have been tested. Compared with traditional thresholding along with edge detector, the JSEG algorithm showed promising result. It offers a relatively higher accuracy and can be used on color image instead of gray image with little computing complexity. A conclusion can be drawn that the JSEG method is suited for imaged wear particle segmentation and can be put into practical use in wear particle’s identification system.
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
Advances in Tribology
Advances in Tribology ENGINEERING, MECHANICAL-
CiteScore
5.00
自引率
0.00%
发文量
1
审稿时长
13 weeks
期刊最新文献
Experimental Comparison of the Effect of Using Synthetic, Semi-Synthetic, and Mineral Engine Oil on Gasoline Engine Parts Wear A Review on the Impact of Bio-Additives on Tribological Behavior of Diesel Fuels Mathematical Modeling of the Bearing Ratio Curve Rmr (50% Rz), through Investigation of the Effect of Process Parameters in Hard Turning of Steel C55 (DIN) with Mixed Ceramics MC2 (Al2O3 + TiC) Tribological and Mechanical Properties of Gradient Coating on Al2O3-Based Coating Produced by Detonation Spraying Methods Investigation on the Cutting Force and Surface Quality in Harmonically Vibrated Broaching (HVB)
×
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