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• W1663371858 abstract "To evaluate an iron ore resource, develop processing routines for iron ore beneficiation, and understand the behavior of the ore during such processing, extensive mineralogical characterizations are required. For calculating mineral associations, mineral liberation, grain size and porosity distribution, and other textural data, reliable imaging techniques are required. Automated optical image analysis (OIA) is a relatively cheap, robust, and objective method for mineral and textural characterization of iron ores and sinters. OIA allows reliable and consistent identification of different iron oxide and oxyhydroxide minerals, e.g., hematite, kenomagnetite, hydrohematite, and vitreous and ochreous goethite, and many gangue minerals in iron ore and different ferrites and silicates in iron ore sinter. OIA also enables a distinction to be made between forms of the same mineral with differing degrees of oxidation or hydration. To reliably identify particles and minerals during OIA, a set of comprehensive procedures should be automatically applied to each processed image. Generally, this includes next stages: image improvement, particle and mineral identification, particle separation, porosity identification, identification of unidentified areas, and correction of mineral maps. This is followed by automated measurements of final mineral maps and statistical processing of results. High resolution, imaging speed, and comprehensive image analysis techniques of modern OIA systems have made it possible to significantly reduce the cost and subjectivity of iron ore and sinter characterization with a simultaneous increase in the accuracy of mineral and textural identification." @default.
• W1663371858 created "2016-06-24" @default.
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• W1663371858 date "2015-01-01" @default.
• W1663371858 modified "2023-10-06" @default.
• W1663371858 title "Automated optical image analysis of natural and sintered iron ore" @default.
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• W1663371858 doi "https://doi.org/10.1016/b978-1-78242-156-6.00004-6" @default.
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