Hyperspectral imaging and subsequent analysis of drill cores is becoming a valuable tool in the mining and mineral exploration industries. Data can be rapidly obtained and spectral analysis avoids subjectivity in mineral identification. However, the core is presented in multiple core trays and separating it from the rock material has proved problematic unless the trays are perfectly aligned.This paper presents a new image processing method for handling this problem. It is robust and insensitive to rotation and contamination of the tray material by dust.

In this paper we explore the use of Baysian belief networks in the prediction of occurrences of geological ore bodies of different types and in different conditions. We show that this approach is consistent with the 'frame-based' modelling approach introduced by A.M. Starfield in a different context.

In this paper we explore the use of Baysian belief networks in the prediction of occurrences of geological ore bodies of different types and in different conditions. We show that this approach is consistent with the 'frame-based' modelling approach Introduced by A.M. Starfield in a different context.