Abstract
Optical image analysis (OIA) supporting microscopic observation can be applied to improve ore mineral characterization of ore deposits, providing accurate and representative numerical support to petrographic studies, on the polished section scale. In this paper, we present an experimental application of an automated mineral quantification process on polished sections from Zaruma-Portovelo intermediate sulfidation epithermal deposit (Ecuador) using multispectral and color images. Minerals under study were gold, sphalerite, chalcopyrite, galena, pyrite, pyrrhotite, bornite, hematite, chalcocite, pentlandite, covellite, tetrahedrite and native bismuth. The aim of the study was to quantify the ore minerals visible in polished section through OIA and, mainly, to show a detailed description of the methodology implemented. Automated ore identification and determination of geometric parameters predictive of geometallurgical behavior, such as grade, grain size or liberation, have been successfully performed. The results show that automated identification and quantification of ore mineral images are possible through multispectral and color image analysis. Therefore, the optical image analysis method could be a consistent automated mineralogical alternative to carry on detailed ore petrography.
Highlights
Ore characterization is important in order to understand the quality and behavior of the material during downstream processing [1,2,3]
We have considered as gold particles mineral phases with sizes bigger than 4 pixels
Optical image analysis (OIA) as a mineralogical quantification tool presents an important advance in ore characterization and predictive metallurgy [16,17]
Summary
Ore characterization is important in order to understand the quality and behavior of the material during downstream processing [1,2,3]. Automated-image identification and quantification of ore minerals and textures together with microscopic description of ore minerals can be applied to improve ore processing and ore deposit characterization [4,5]. Optical image analysis (OIA) is an automated mineralogical process and represents an important advance over traditional techniques (point counting) in the characterization of objects (ore minerals) in polished sections [6,7,8,9,10,11,12]. Nowadays, automated mineralogy is used for ore characterization, process design and the optimization of both. Other automated mineralogical methods and tools, such as the mineral liberation analyzer (MLA) and the quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) are widely used
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
