An automatic HyLoggerTM mineral mapping method using a machine-learning-based computer vision technique. Issue 7 (3rd October 2019) - Liu, J.; Chen, W.; Muller, M.; Chalup, S.; Wheeler, C.
Abstract: HyLogger profile scanning is commonly utilised for drill-core logging but the limited scanning area may not detect all important geological features. The study presented in this paper aims to develop a mineral mapping solution for this core-logging process by leveraging the colour image captured during the scanning process. A machine-learning-based computer vision program was developed by implementing a k -means clustering and a global colour profiling algorithm. A suite of drill-core images was used to validate the developed program. Results indicate that there is a direct correlation between the mineral assemblage of a rock type and its colour specifications. The identified mineral type and relative abundance were comparable with HyLogger scan results.