An adaptive clustering algorithm for color quantization
Pattern Recognition Letters
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Facts, Conjectures, and Improvements for Simulated Annealing
Facts, Conjectures, and Improvements for Simulated Annealing
Ant colony optimization of clustering models: Research Articles
International Journal of Intelligent Systems
GA-fuzzy modeling and classification: complexity and performance
IEEE Transactions on Fuzzy Systems
Morphological segmentation and classification of marble textures at macroscopical scale
Computers & Geosciences
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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.