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Journals / Journal of Soft Computing and Artificial Intelligence / 2023 / Cilt: 4 Sayı: 1

A Review on Measurement of Particle Sizes by Image Processing Techniques

Vahit TONGUR
Ahmet Burçin BATIBAY
Murat KARAKOYUN
Pages
15–28
Publication Date
2023-06-25
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In this review, a comparative analysis was made by examining recent studies on particle size measurement.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This review is based on how to measure particle sizes with different image processing techniques.
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Key Findings & Data:In addition to this, particle size significantly affects the mechanical properties of the material.
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Conclusion & Impact:In this review, a comparative analysis was made by examining recent studies on particle size measurement.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Image processing · Measurement · Particle Size

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.

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Cite This Article

TONGUR, V., BATIBAY, A. B., KARAKOYUN, M. (2023). A Review on Measurement of Particle Sizes by Image Processing Techniques. Journal of Soft Computing and Artificial Intelligence, Cilt: 4 Sayı: 1, 15–28. https://ajindex.com/articles/952508

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References (5)

  1. G. González and C. L. Evans, "Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline: Data architecture, artificial intelligence, automated processing, containerization, and clusters orchestration ease the transition from data acquisition to insights in medium‐to‐large datasets," BioEssays, vol. 41, no. 6, p. 1900004, 2019. X. Zhang and W. Dahu, "Application of artificial intelligence algorithms in image processing," Journal of Visual Communication and Image Representation, vol. 61, pp. 42-49, 2019.
  2. S. Robertson, H. Azizpour, K. Smith, and J. Hartman, "Digital image analysis in breast pathology—from image processing techniques to artificial intelligence," Translational Research, vol. 194, pp. 19-35, 2018. O. E. Akay and M. Das, "Modeling the total heat transfer coefficient of a nuclear research reactor cooling system by different methods," Case Studies in Thermal Engineering, vol. 25, p. 100914, 2021.
  3. S. V. Seyedin, S. H. Seyedin, and A. S. Seyedin, "Designing and programming an efficient software for sizing and counting various particles using image processing technique," BRAIN. Broad Research in Artificial Intelligence and Neuroscience, vol. 10, no. 2, pp. 103-118, 2019. S. Al-Thyabat and N. Miles, "An improved estimation of size distribution from particle profile measurements," Powder Technology, vol. 166, no. 3, pp. 152-160, 2006. I. Kursun, "Particle size and shape characteristics of kemerburgaz quartz sands obtained by sieving, laser diffraction, and digital image processing methods," Mineral Processing & Extractive Metallurgy Review, vol. 30, no. 4, pp. 346-360, 2009.
  4. E. Emil Kaya, O. Kaya, G. Alkan, S. Gürmen, S. Stopic, and B. J. M. Friedrich, "New proposal for size and size-distribution evaluation of nanoparticles synthesized via ultrasonic spray pyrolysis using search algorithm based on image-processing technique," vol. 13, no. 1, p. 38, 2020.
  5. A. Nazar, F. Silva, and J. Ammann, "Image processing for particle characterization," Materials characterization, vol. 36, no. 4-5, pp. 165-173, 1996. S. Beucher, "Use of watersheds in contour detection," in Proceedings of the International Workshop on Image Processing, 1979: CCETT. K. S. Naphade, "Soil characterization using digital image processing," Lehigh University, 1999. L. C. Wu and C. Yu, "Powder particle size measurement with digital image processing using Matlab," in Advanced Materials Research, 2012, vol. 443, pp. 589-593: Trans Tech Publ. X. Li et al., "Aut