Abstract
Automatic classification of objects based on their visual appearance is often performed based on clustering algorithms, which can be based on soft computing techniques. One of the most used methods is fuzzy clustering. However, this method can converge to local minima. This problem has been addressed very recently by applying ant colony optimization to tackle this problem. This paper proposed the use of this fuzzy-ant clustering approach to derive fuzzy models. These models are used to classify marbles based on their visual appearance; color and vein classification is performed. The proposed fuzzy modeling approach is compared to other soft computing classification algorithms, namely: fuzzy, neural, simulated annealing, genetic and combinations of these approaches. Fuzzy-ant models presented higher classification rates than the other soft computing techniques.
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Vieira, S.M., Sousa, J.M.C., Pinto, J.R.C. (2006). Ant Based Fuzzy Modeling Applied to Marble Classification. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2006. Lecture Notes in Computer Science, vol 4142. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11867661_9
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DOI: https://doi.org/10.1007/11867661_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44894-5
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