Abstract
A multidisciplinary methodology that goes from the extraction of features till the classification of a set of different granites is presented in this paper. The set of tools to extract the features that characterise the polished surfaces of granites is mainly based on mathematical morphology. The classification methodology is based on a genetic algorithm capable of searching for the input feature space used by the nearest neighbour rule classifier. Results show that is adequate to perform feature reduction and simultaneously improve the recognition rate. Moreover, the present methodology represents a robust strategy to understand the proper nature of the textures studied and their discriminant features.
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Ramos, V., Pina, P. (2005). Exploiting and Evolving RN Mathematical Morphology Feature Spaces. In: Ronse, C., Najman, L., Decencière, E. (eds) Mathematical Morphology: 40 Years On. Computational Imaging and Vision, vol 30. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3443-1_42
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DOI: https://doi.org/10.1007/1-4020-3443-1_42
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