In this study, an intelligent system for mineral identification in thin sections is proposed
based on RGB and HSI color spaces and texture features in plane and cross polarized light.
The proposed system has two phases for mineral identification. In phase# 1, which is the
segmentation phase, 12 color components are extracted for each pixel, and using an
incremental clustering algorithm, several mineral clusters including index mineral are
produced. Afterwards, in phase# 2 which is the identification phase, the produced mineral …