Integration and Analysis of Optical and Sem-Based Microscopy for Automated Mineralogical Characterisation

Abstract

Digital optical microscopy (DOM) and automated scanning electron microscopy (ASEM)-based mineralogy systems (MLA, QEMSCAN) have undergone significant developments within the last decade. However, the two mineralogical techniques have not yet been integrated to combine the strengths of both analytical platforms. Major advances in DOM in the last few years have provided important new capabilities with potential applications to automated mineralogy. The advent of DOM offers significantly more automated mineralogy capabilities than traditional expert-mineralogist driven optical microscopy. This current research involves non-linear image registration and transfer of mineralogical identification from ASEM to DOM systems using sophisticated image manipulation and data analysis software. Data integration involves creation of a library linking optical property variability data with mineral identification using ASEM, thus reducing reliance on skilled manual optical mineral identification. Image fusion is demonstrated using an example where sulphides are mapped and classified using ASEM combined with gangue mineralogy obtained from DOM images.