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Quantitative measures for shape and size of particles

Abstract: Previous efforts to define these terms are reviewed and their deficiencies noted. New quantitative measures of size and shape are proposed, based upon measurements made possible by image analysis techniques. These may be applied to both single particle and to assemblages of particles. Laboratory test results are presented to demonstrate the application of one of the new measures. Suggestions are made for further research.

Keywords:Quantitative measuresParticle shapeParticle size

https://doi.org/10.1016/S0032-5910(01)00476-4



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Development of a rapid measurement system for coarse aggregate morphological parameters

Highlights

  • A new algorithm (the fitted-ellipse method) evaluates the angularity of aggregates.
  • Using a linear profile scanner improves the measurement accuracy of the angularity.
  • It is possible to measure the morphological parameters accurately and quickly.
  • A linear profile scanner combined with a CCD camera is suited to batch inspections.

Abstract:Morphological parameters of coarse aggregates, including the angularity index (AI), flat and elongated ratio, flatness ratio, and sphericity, strongly affect the performance of asphalt concrete. A device must be developed to efficiently and accurately measure these parameters. Herein, a charge-coupled device camera and a linear profile scanner are combined to evaluate the parameters. The AI is calculated using three methods. The results show that the fitted-ellipse method provides superior results among the three AI measurement methods. Moreover, the use of a linear profile scanner improves the AI measurement accuracy. Therefore, the proposed combination has high measurement efficiency and is suitable for batch inspections.

Keywords:Charge-coupled device cameraLinear profile scannerAngularityFlatness ratioSphericity

https://doi.org/10.1016/j.partic.2019.06.006



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Sphericity, shape factor, and convexity measurement of coarse aggregate for concrete using digital image processing

Abstract: A method of measuring the sphericity, shape factor, and convexity of coarse aggregate for concrete using digital image processing (DIP) is developed. Unlike other DIP methods, this method is capable of estimating the thickness and volume of the particles, and can thus be used to measure shape parameters dependent on thickness and to evaluate weighted mean values of the shape parameters of the individual particles in an aggregate sample. A total of 46 rock aggregate samples obtained from five different sources derived from three different types of rock have been analyzed by the method and the shape parameters so measured are correlated to the traditional measure of angularity with the hope of identifying shape parameters that may be used as direct measures of angularity. Several shape parameters are found to have good correlation with the traditional measure of angularity but among them, only the convexity ratio and fullness ratio may be used as measures of angularity. Lastly, it is advocated that the traditional measure of angularity in terms of packing density should be abandoned; packing density by itself is an important indicator of aggregate performance but is not a good measure of angularity.

Keywords: AggregateCoarse aggregate for concreteDigital image processingPacking densityParticle shape analysis

https://doi.org/10.1016/S0008-8846(99)00259-8



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图像分析的颗粒形状参数描述

摘要:本文较全面地介绍了在颗粒形状分析中常用的参数,并在实际应用和比较分析的基础上指出,利用颗粒面积和周长得到的参数S11是描述颗粒形状效果比较好的参数之一。笔者结合试验中的实际应用,介绍了该参数的使用方法。

关键词:颗粒;形状系数;图像分析

2004,26(5): 659-662



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Selection of Descriptors for Particle Shape Characterization

Abstract: Conventional shape descriptors, formed from a ratio of two particle size measurements, are among the simplest of the many methods used for quantitative particle shape characterization. However, a significant limitation of using one of these shape descriptors is that its value is often not unique to a specific shape. Use of several different shape descriptors may circumvent this problem but, as particle size can be defined in a large number of ways, a similarly large number of shape descriptors can be defined. While some differ substantially, others are only subtly different, conveying similar information. Thus, it is not obvious which of the many possible descriptors should be utilized. In this paper, two-dimensional particle shape descriptors obtained by image analysis of six different commercially sourced powders were considered. Techniques of cluster and correlation analysis were applied to assist in identifying redundant descriptors for shape characterization of these powder particles, allowing for efficient description of shape using a reduced set. It was found that at least two descriptors are required: aspect ratio and the square root of form factor. Significantly, each descriptor is most sensitive to a different attribute of shape: elongation and ruggedness, respectively.

Keywords: cluster analysis, conventional shape descriptors, particle shape

Part. Part. Syst. Charact. 20 (2003) 25 ± 38