Automatic classification of granite tiles through colour and texture features

Authors:
Francesco Bianconi;Elena González;Antonio Fernández;Stefano A. Saetta
Affiliations:
Universití degli Studi di Perugia, Dipartimento Ingegneria Industriale, Via G. Duranti 67 - 06125 Perugia, Italy;Universidade de Vigo, Escuela de Ingeniería Industrial, Campus Universitario - 36310 Vigo, Spain;Universidade de Vigo, Escuela de Ingeniería Industrial, Campus Universitario - 36310 Vigo, Spain;Universití degli Studi di Perugia, Dipartimento Ingegneria Industriale, Via G. Duranti 67 - 06125 Perugia, Italy
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

This paper is about the development of an expert system for automatic classification of granite tiles through computer vision. We discuss issues and possible solutions related to image acquisition, robustness against noise factors, extraction of visual features and classification, with particular focus on the last two. In the experiments we compare the performance of different visual features and classifiers over a set of 12 granite classes. The results show that classification based on colour and texture is highly effective and outperforms previous methods based on textural features alone. As for the classifiers, Support Vector Machines show to be superior to the others, provided that the governing parameters are tuned properly.