Intelligent color image analysis of sintered ores for simple and rapid determination of Fe3O4 concentration

Abstract

A simple determination of the Fe3O4 concentrations of sintered ores using color images of the samples has been explored. Sintered ore is mainly composed of Fe2O3 (red), Fe3O4 (black), and other white inorganic oxides, so the color of sintered ore could be representative of the relative abundance of the constituents. Two important challenges were addressed to achieve reliable quantitative color image analysis. First, minute dents and bumps (embosses) exist on the sample surface due to inconsistent particle sizes and particle agglomeration, thereby generating dark shadows. Second, small white spots corresponding to inorganic oxide particles were spread throughout acquired images. The white spots yield very high RGB values, which would hamper the translation of the real sample color originating from the iron oxides. Therefore, the segmentations of particle agglomeration-induced shadows and white spots in the sample images were separately executed using Otsu's method and modified fuzzy C-means (MFCM), respectively. Then, color moments and derived variables from the segmented images were employed to determine Fe3O4 concentrations (6.5–10.5 wt%) using extreme gradient boosting (XGBoost). The predicted concentrations from the color analysis correlated well with reference concentrations determined using conventional titration, with a root mean square error of prediction (RMSEP) of 0.39 wt%.