Automated Optical Image Analysis of Iron Ore Sinter

Sinter quality is a key element for stable blast furnace operation. strength and reducibility depend considerably on the mineral composition associated textural features. During sinter optical image analysis (OIA), it important to distinguish different morphologies of same such as primary/secondary hematite, types silico-ferrite calcium aluminum (SFCA). Standard red, green blue (RGB) thresholding cannot effectively segment one from another. The Commonwealth Scientific Industrial Research Organization’s (CSIRO) OIA software Mineral4/Recognition4 incorporates unique identification module allowing various textures/morphologies be discriminated. Together with other capabilities software, this feature was used examination iron ore sinters where ability hematite (primary versus secondary), morphological sub-types SFCA (platy prismatic), common phases magnetite, larnite, glass remnant aluminosilicates crucial quantifying petrology. Three samples were examined. Visual comparison showed very high correlation between manual automated phase identification. results also gave correlations point counting, X-ray Diffraction (XRD) Fluorescence (XRF) results. classification performed by Recognition4 potential deep understanding properties changes under sintering conditions.