• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied clay science >Quantification and characterization of microporosity by image processing, geometric measurement and statistical methods: Application on SEM images of clay materials1^
【24h】

Quantification and characterization of microporosity by image processing, geometric measurement and statistical methods: Application on SEM images of clay materials1^

机译：通过图像处理，几何测量和统计方法对微孔进行定量和表征：在粘土材料的SEM图像中的应用1 ^

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A series of image processing technologies and geometric measurement methods is introduced to quantify multiple scale microporosity in images. All the operations are non-destructive so as to ensure the accuracy of the results. With the application of these methods, various basic geometric parameters of the pores can be computed automatically in the computer, such as area, perimeter, direction etc. On the basis of these geometric parameters, probability entropy, probability distribution index and fractal dimension were introduced to describe the distribution of the three major characteristics of pore system, direction, area and form factor, respectively. Computer software developed on the basis of these methods was used to quantify the SEM images of clay samples during shear test. According to the quantification result, total pore area and average pore form factor reduce during the test. The variation of pore area and form factor is related to probability distribution index and fractal dimension, which indicates the variation of microstructures between pores. Error analysis shows that the deviation using the image processing is within 5%, and the deviations of statistical parameters are smaller in comparison with those of basic geometric parameters. The statistical methods are adapted to the quantification of 2D multiple scale objects. This paper offers a reliable basis for the quantification and characterization of microporosity by image processing.
机译：引入了一系列图像处理技术和几何测量方法来量化图像中的多尺度微孔率。所有操作都是非破坏性的，以确保结果的准确性。利用这些方法，可以在计算机中自动计算出孔的各种基本几何参数，例如面积，周长，方向等。在这些几何参数的基础上，引入了概率熵，概率分布指数和分形维数。描述孔隙系统的三个主要特征的分布，分别是方向，面积和形状因子。在这些方法的基础上开发的计算机软件被用来量化剪切试验期间粘土样品的SEM图像。根据定量结果，总孔面积和平均孔形因数在测试过程中减小。孔面积和形状因子的变化与概率分布指数和分形维数有关，表明孔之间的微观结构变化。误差分析表明，采用图像处理的偏差在5％以内，与基本几何参数相比，统计参数的偏差较小。统计方法适用于2D多尺度对象的量化。本文为图像处理中微孔的定量和表征提供了可靠的依据。

著录项

  • 来源
    《Applied clay science》 |2011年第1期|p.97-106|共10页
  • 作者

    Chun Liu; Bin Shi; Jian Zhou; Chaosheng Tang;

  • 作者单位

    School of Earth Sciences and Engineering, Nanjing University, Nanjing 210093, PR China,Department of Geological and Environmental Sciences, Stanford University, CA 94305, USA;

    School of Earth Sciences and Engineering, Nanjing University, Nanjing 210093, PR China;

    Ceotechnical engineering institute of Zhejiang University, Hangzhou 310058, PR China;

    School of Earth Sciences and Engineering, Nanjing University, Nanjing 210093, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    micropore; image processing; quantitative analysis; statistical method; SEM;

    机译：微孔图像处理;定量分析;统计方法;扫描电镜;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号