Rock Image Classification Using Non-Homogenous Textures and Spectral Imaging

Abstract

Texture analysis and classification are usual tasks in pattern recognition. Rock texture is a demanding classification task, because the texture is often non-hom ogenous. In this paper, we introduce a rock texture classification method, which is based on textural and spectral features of the rock. The spectral features are considered as some color parameters whereas the textural features are calculated from the co-occurrence matrix. In this classification method, non-homogenous texture imag es are divided into blocks. The feature values are calculated for each block separately. In this way, the feature values of the texture image can be presented as a feature histogram. The classification method is tested using two types of rock textures. The experimental results show that the proposed features are able to distinguish rock textures quite well.