Embedded Particle Size Measurement Method of Metal Mineral Polished Section Using Gaussian Mixture Model Based on Expectation Maximization Algorithm

Abstract

The study of process mineralogy plays a very important role in the field of mineral processing and metallurgy, in which the measurement of mineral-embedded particle size is one of the main research areas. The manual measurement method using a microscope has many problems, such as heavy workload and low measurement accuracy. In order to solve this problem, this paper proposes a Gaussian mixture model based on an expectation maximization (EM) algorithm to measure the embedded particle sizes of minerals of polished metal sections. Experiments are here performed on the polished section images of ilmenite and pyrite, and we compared the results with a microscope. The experimental results show that the proposed method has higher precision and accuracy in measuring the embedded particle sizes of metal minerals.