METHOD OF PARTICLE CHARACTERISATION; MORPHOLOGY BY IMAGE ANALYSIS

被引:0
|
作者
Belaroui, K. [1 ]
Pons, M. N. [2 ]
机构
[1] Univ Sci & Technol Med BOUDIAF dOran USTO MB, Lab STGP, BP 1505, El Mnouer Oran, Algeria
[2] CNRS, UPR 3349, Lab React & Genie Proc, F-54001 Nancy, France
关键词
Characterization; particle size; morphology; image analysis; porous media;
D O I
暂无
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The aim of our work is to establish a morphological characterization of particles. The particle size analysis determines the size distribution of a population of particles using a laser granulometer device. The evolution of particle size distributions is complemented by a study on the particle shape. Thus, morphological analysis consists to acquire images of the particles by using a scanning electron microscopy which will be then processed using an algorithm. The treatment is a set of operations that are thresholding, erosion, expansion and reconstruction of the image. Data processing is performed based on a set of dimensional parameters.
引用
收藏
页码:192 / 201
页数:10
相关论文
共 50 条
  • [1] Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method
    Lu, Zhaolin
    Hu, Xiaojuan
    Lu, Yao
    INTERNATIONAL JOURNAL OF ANALYTICAL CHEMISTRY, 2017, 2017
  • [2] A particle morphology characterization system and its method based on particle scattering image recognition
    Ding, Xinrui
    Liu, Xin
    Shao, Changkun
    Chen, Bowen
    Li, Weihong
    Li, Zongtao
    OPTICS AND LASERS IN ENGINEERING, 2023, 163
  • [3] Application of image stitching method in corrosion morphology analysis
    Zhang, Shouxin
    Li, Zili
    Yang, Chao
    Xu, Yazhou
    Zhou, Jiayu
    JOURNAL OF ELECTRONIC IMAGING, 2019, 28 (01)
  • [4] Semi-automatic image analysis of particle morphology of cellulose nanocrystals
    Sezen Yucel
    Robert J. Moon
    Linda J. Johnston
    Berkay Yucel
    Surya R. Kalidindi
    Cellulose, 2021, 28 : 2183 - 2201
  • [5] Semi-automatic image analysis of particle morphology of cellulose nanocrystals
    Yucel, Sezen
    Moon, Robert J.
    Johnston, Linda J.
    Yucel, Berkay
    Kalidindi, Surya R.
    CELLULOSE, 2021, 28 (04) : 2183 - 2201
  • [6] Characterisation of Bleached Hemp Pulps with the Use of the Computer Image Analysis Method
    Danielewicz, Dariusz
    Surma-Slusarska, Barbara
    FIBRES & TEXTILES IN EASTERN EUROPE, 2011, 19 (02) : 96 - 101
  • [7] Utilization of optical image analysis and automatic texture classification for iron ore particle characterisation
    Donskoi, E.
    Suthers, S. P.
    Fradd, S. B.
    Young, J. M.
    Campbell, J. J.
    Raynlyn, T. D.
    Clout, J. M. F.
    MINERALS ENGINEERING, 2007, 20 (05) : 461 - 471
  • [8] Image analysis framework with focus evaluation for in situ characterisation of particle size and shape attributes
    Cardona, Javier
    Ferreira, Carla
    McGinty, John
    Hamilton, Andrew
    Agimelen, Okpeafoh S.
    Cleary, Alison
    Atkinson, Robert
    Michie, Craig
    Marshall, Stephen
    Chen, Yi-Chieh
    Sefcik, Jan
    Andonovic, Ivan
    Tachtatzis, Christos
    CHEMICAL ENGINEERING SCIENCE, 2018, 191 : 208 - 231
  • [9] Morphology and particle size (MaPS) exercise: testing the applications of image analysis and morphology descriptions for nuclear forensics
    Dunn, Stuart A.
    Schwerdt, Ian J.
    Meier, David E.
    Marks, Naomi E.
    Shaw, Thomas
    Hanson, Alexa
    Sentz, Kari
    Said, Meena
    Clark, Richard A.
    Makovsky, Kyle A.
    Lonergan, Jason M.
    Gilbert, Matthew
    JOURNAL OF RADIOANALYTICAL AND NUCLEAR CHEMISTRY, 2024, 333 (04) : 2163 - 2181
  • [10] Morphology and particle size (MaPS) exercise: testing the applications of image analysis and morphology descriptions for nuclear forensics
    Stuart A. Dunn
    Ian J. Schwerdt
    David E. Meier
    Naomi E. Marks
    Thomas Shaw
    Alexa Hanson
    Kari Sentz
    Meena Said
    Richard A. Clark
    Kyle A. Makovsky
    Jason M. Lonergan
    Matthew Gilbert
    Journal of Radioanalytical and Nuclear Chemistry, 2024, 333 : 2163 - 2181