Open AccessAutomatic characterization of iron ore by digital microscopy and image analysis
Author(s) -
Julio César Álvarez Iglesias,
Karen Soares Augusto,
Otávio da Fonseca Martins Gomes,
Alei Leite Alcântara Domingues,
Maria Beatriz Vieira,
Catia Casagrande,
Sidnei Paciornik
Publication year - 2018
Publication title -
journal of materials research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.832
H-Index - 44
eISSN - 2214-0697
pISSN - 2238-7854
DOI - 10.1016/j.jmrt.2018.06.014
Subject(s) - materials science , hematite , characterization (materials science) , microscopy , lamellar structure , microscope , crystallite , polarized light microscopy , optical microscope , digital image , mineralogy , image processing , artificial intelligence , optics , metallurgy , image (mathematics) , nanotechnology , computer science , geology , scanning electron microscope , composite material , physics
This paper presents an automatic system for mineralogical and textural characterization of iron ores based on digital microscopy and image analysis. It employs a motorized and computer-controlled reflected light microscope in a correlative approach that combines bright field and circular polarization modes. Mosaic images covering large areas of polished sections are acquired to image thousands of particles. Different classifiers discriminate compact and non-compact hematite, polycrystalline and monocrystalline particles, and identify particles as granular, lamellar, and lobular. The entire process is automatic and produces a full pdf report containing typical images and the quantification of mineral and textural phases.
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