Abstract
A novel methodology for the automatic classification of the different textural classes that constitute a rock at the macroscopic scale is presented in this paper. The methodology starts with the segmentation of elementary textural units of the image followed by their classification, whose feature space partition results from the geometric modelling of the training sets. This approach uses mainly mathematical morphology operators and is tested with images of macroscopic polished surfaces of 14 types of portuguese grey granites.
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Pina, P., Barata, T. (2003). Petrographic Classification at the Macroscopic Scale Using a Mathematical Morphology Based Approach. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_88
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DOI: https://doi.org/10.1007/978-3-540-44871-6_88
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