Quantification of the Mineral Phases in Iron Ore Sinters From Gray Historgram of Micrograph

An intelligent recognition and quantification system for the micrographs iron ore sinter was developed in the current paper. The average distribution parameters in a gray histogram of minerals by a Gaussian gray distribution model were obtained. The feature curves of the gray histogram of two minerals were achieved by combining the two density functions. The feature indexes, such as the number and position of the peaks and the valleys of two minerals in different ratios, were quantified by differentiating the distribution functions. This algorithm is able to extract the feature of the minerals adequately and accurately for recognizing the composition and phases of the minerals intelligently.