用图像处理技术测量颗粒尺寸的研究进展

IF 3.3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Artificial Intelligence and Soft Computing Research Pub Date : 2023-02-17 DOI:10.55195/jscai.1218662
Vahit Tongur, A. B. Batibay, Murat Karakoyun
{"title":"用图像处理技术测量颗粒尺寸的研究进展","authors":"Vahit Tongur, A. B. Batibay, Murat Karakoyun","doi":"10.55195/jscai.1218662","DOIUrl":null,"url":null,"abstract":"This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the material. In material science, structure of the material is analyzed to understand that a material can provide certain standards, such as toughness and durability. Therefore, it is a great importance to make this measurement carefully and accurately. The segmentation approach, which is frequently used in image processing, aims to isolate objects in an image from the background. In this sense, the separation of particles from the background can be considered as a problem of the image processing. In image processing applications, there are different approaches used in segmentation such as histogram-based, clustering-based, region amplification, separation and merging. In this review, a comparative analysis was made by examining recent studies on particle size measurement.","PeriodicalId":48494,"journal":{"name":"Journal of Artificial Intelligence and Soft Computing Research","volume":"9 10-11 1","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review on Measurement of Particle Sizes by Image Processing Techniques\",\"authors\":\"Vahit Tongur, A. B. Batibay, Murat Karakoyun\",\"doi\":\"10.55195/jscai.1218662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the material. In material science, structure of the material is analyzed to understand that a material can provide certain standards, such as toughness and durability. Therefore, it is a great importance to make this measurement carefully and accurately. The segmentation approach, which is frequently used in image processing, aims to isolate objects in an image from the background. In this sense, the separation of particles from the background can be considered as a problem of the image processing. In image processing applications, there are different approaches used in segmentation such as histogram-based, clustering-based, region amplification, separation and merging. In this review, a comparative analysis was made by examining recent studies on particle size measurement.\",\"PeriodicalId\":48494,\"journal\":{\"name\":\"Journal of Artificial Intelligence and Soft Computing Research\",\"volume\":\"9 10-11 1\",\"pages\":\"\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2023-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Artificial Intelligence and Soft Computing Research\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.55195/jscai.1218662\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence and Soft Computing Research","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.55195/jscai.1218662","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

摘要

这篇综述是基于如何测量颗粒大小与不同的图像处理技术。除此之外,粒度对材料的机械性能也有显著的影响。在材料科学中,分析材料的结构以了解材料可以提供某些标准,例如韧性和耐久性。因此,仔细准确地进行这一测量是非常重要的。分割方法是一种常用的图像处理方法,其目的是将图像中的物体与背景分离开来。从这个意义上说,粒子与背景的分离可以看作是图像处理的一个问题。在图像处理应用中,有不同的分割方法,如基于直方图、基于聚类、区域放大、分离和合并。本文对近年来有关粒径测量的研究进行了比较分析。
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
A Review on Measurement of Particle Sizes by Image Processing Techniques
This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the material. In material science, structure of the material is analyzed to understand that a material can provide certain standards, such as toughness and durability. Therefore, it is a great importance to make this measurement carefully and accurately. The segmentation approach, which is frequently used in image processing, aims to isolate objects in an image from the background. In this sense, the separation of particles from the background can be considered as a problem of the image processing. In image processing applications, there are different approaches used in segmentation such as histogram-based, clustering-based, region amplification, separation and merging. In this review, a comparative analysis was made by examining recent studies on particle size measurement.
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
Journal of Artificial Intelligence and Soft Computing Research
Journal of Artificial Intelligence and Soft Computing Research COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
7.00
自引率
25.00%
发文量
10
审稿时长
24 weeks
期刊介绍: Journal of Artificial Intelligence and Soft Computing Research (available also at Sciendo (De Gruyter)) is a dynamically developing international journal focused on the latest scientific results and methods constituting traditional artificial intelligence methods and soft computing techniques. Our goal is to bring together scientists representing both approaches and various research communities.
期刊最新文献
Bending Path Understanding Based on Angle Projections in Field Environments Self-Organized Operational Neural Networks for The Detection of Atrial Fibrillation Interpreting Convolutional Layers in DNN Model Based on Time–Frequency Representation of Emotional Speech A Few-Shot Learning Approach for Covid-19 Diagnosis Using Quasi-Configured Topological Spaces Metrics for Assessing Generalization of Deep Reinforcement Learning in Parameterized Environments
×
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